PyTorch Tutorial

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tutorial_.ipynb_checkpoints_nn_tutorial-checkpoint.ipynb

tutorial_.ipynb_checkpoints_torch_object_detection-checkpoint.ipynb

tutorial_.ipynb_checkpoints_torch_tensorboard-checkpoint.ipynb

tutorial_.ipynb_checkpoints_torch_transferlearning-checkpoint.ipynb

tutorial_05_gradients_numpy.py

import numpy as np

X = np.array([1, 2, 3, 4], dtype=np.float32)
Y = np.array([2, 4, 6, 8], dtype=np.float32)

w = 0.0


# model prediction
def forward(x):
    return w * x


# loss = MSE
def loss(y, y_predicted):
    return ((y_predicted - y) ** 2).mean()


# gradient
# MSE = 1/N * (w*x - y)**2
# dJ/dw = 1/N 2x (w*x - y)
def gradient(x, y, y_predicted):
    return np.dot(2*x, y_predicted - y).mean()


print(f'Prediction before training: f(5) = {forward(5):.3f}')

# training
learning_rate = 0.01
n_iters = 20

for epoch in range(n_iters):
    # prediction
    y_pred = forward(X)

    # loss
    l = loss(Y, y_pred)

    # gradients
    dw = gradient(X, Y, y_pred)

    # update weights
    w -= learning_rate * dw

    if epoch % 2 == 0:
        print(f'epoch {epoch+1}: w = {w:.3f}, loss = {l:.8f}')

print(f'Prediction after training: f(5) = {forward(5):.3f}')

tutorial_05_gradients_torch.py

import numpy as np
import torch

X = torch.tensor([1, 2, 3, 4], dtype=torch.float32)
Y = torch.tensor([2, 4, 6, 8], dtype=torch.float32)

w = torch.tensor(0.0, dtype=torch.float32, requires_grad=True)


# model prediction
def forward(x):
    return w * x


# loss = MSE
def loss(y, y_predicted):
    return ((y_predicted - y) ** 2).mean()


print(f'Prediction before training: f(5) = {forward(5):.3f}')

# training
learning_rate = 0.01
n_iters = 100

for epoch in range(n_iters):
    # prediction
    y_pred = forward(X)

    # loss
    l = loss(Y, y_pred)

    # gradients
    l.backward() #dl/dw

    # update weights
    with torch.no_grad():
        w -= learning_rate * w.grad

    # zero gradients
    w.grad.zero_()

    if epoch % 10 == 0:
        print(f'epoch {epoch+1}: w = {w:.3f}, loss = {l:.8f}')

print(f'Prediction after training: f(5) = {forward(5):.3f}')

tutorial_06_training_pipeline.py

# 1) Design model (input, output size, forward pass)
# 2) construct loss and optimizer
# 3) Training loop
#   -- forward pass: compute prediction
#   -- backward pass: gradients
#   -- update weights

import torch
import torch.nn as nn

X = torch.tensor([[1], [2], [3], [4]], dtype=torch.float32)
Y = torch.tensor([[2], [4], [6], [8]], dtype=torch.float32)

X_test = torch.tensor([5], dtype = torch.float32)

n_samples, n_features = X.shape
print(n_samples, n_features)

input_size = n_features
output_size = n_features

#model = nn.Linear(input_size, output_size)

class LinearRegression(nn.Module):

    def __init__(self, input_dim, output_dim):
        super(LinearRegression, self).__init__()
        #define layers
        self.lin = nn.Linear(input_dim, output_dim)

    def forward(self, x):
        return self.lin(x)

model = LinearRegression(input_size, output_size)

print(f'Prediction before training: f(5) = {model(X_test).item():.3f}')

# training
learning_rate = 0.01
n_iters = 100

loss = nn.MSELoss()
optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)

for epoch in range(n_iters):
    # prediction
    y_pred = model(X)

    # loss
    l = loss(Y, y_pred)

    # gradients
    l.backward() #dl/dw

    # update weights
    optimizer.step()

    # zero gradients
    optimizer.zero_grad()

    if epoch % 10 == 0:
        w, b = model.parameters()
        print(f'epoch {epoch+1}: w = {w[0][0].item():.3f}, loss = {l:.8f}')

print(f'Prediction after training: f(5) = {model(X_test).item():.3f}')

tutorial_07_linear_regression.py

# 1) Design model (input, output size, forward pass)
# 2) construct loss and optimizer
# 3) Training loop
#   -- forward pass: compute prediction
#   -- backward pass: gradients
#   -- update weights

import torch
import torch.nn as nn
import numpy as np
from sklearn import datasets
import matplotlib.pyplot as plt

# 0) prepare data
X_numpy, y_numpy = datasets.make_regression(n_samples = 100, n_features = 1, noise = 20, random_state = 1)

# cast to float Tensor
X = torch.from_numpy(X_numpy.astype(np.float32))
y = torch.from_numpy(y_numpy.astype(np.float32))
y = y.view(y.shape[0], 1)

n_samples, n_features = X.shape
# 1) model
input_size = n_features
output_size = 1
model= nn.Linear(input_size, output_size)

# 2) loss and optimizer
learning_rate = 0.01
criterion = nn.MSELoss()
optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)

# 3) training loop
num_epochs = 100
for epoch in range(num_epochs):
    # forward pass and loss
    y_predicted = model(X)
    loss = criterion(y_predicted, y)

    # backward pass
    loss.backward()

    # update
    optimizer.step()

    optimizer.zero_grad()

    if (epoch+1) % 10 == 0:
        print(f'epoch: {epoch+1}, loss = {loss.item}:.4f')

# plot
predicted = model(X).detach().numpy()
plt.plot(X_numpy, y_numpy, 'ro')
plt.plot(X_numpy, predicted, 'b')
plt.show()

tutorial_08_logistic_regression.py

# 1) Design model (input, output size, forward pass)
# 2) construct loss and optimizer
# 3) Training loop
#   -- forward pass: compute prediction
#   -- backward pass: gradients
#   -- update weights

import torch
import torch.nn as nn
import numpy as np
from sklearn import datasets
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split

# 0) prepare the data
bc = datasets.load_breast_cancer()
X, y = bc.data, bc.target

n_samples, n_features = X.shape
print(n_samples, n_features)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1234)

# scale
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)

X_train = torch.from_numpy(X_train.astype(np.float32))
X_test = torch.from_numpy(X_test.astype(np.float32))
y_train = torch.from_numpy(y_train.astype(np.float32))
y_test = torch.from_numpy(y_test.astype(np.float32))

y_train = y_train.view(y_train.shape[0], 1)
y_test = y_test.view(y_test.shape[0], 1)


# 1) model
# f = wx + b, sigmoid at the end
class LogisticRegression(nn.Module):

    def __init__(self, n_input_features):
        super(LogisticRegression, self).__init__()
        self.linear = nn.Linear(n_input_features, 1)

    def forward(self, x):
        y_predicted = torch.sigmoid(self.linear(x))
        return y_predicted


model = LogisticRegression(n_features)

# 2) loss and optimizer
learning_rate = 0.01
criterion = nn.BCELoss()
optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)

# 3) training loop
num_epochs = 200
for epoch in range(num_epochs):
    # forward pass and loss
    y_predicted = model(X_train)
    loss = criterion(y_predicted, y_train)

    # backward
    loss.backward()

    # update
    optimizer.step()

    # zero gradients
    optimizer.zero_grad()

    if (epoch + 1) % 10 == 0:
        print(f'epoch: {epoch + 1}, loss = {loss.item():.4f}')

with torch.no_grad():
    y_predicted = model(X_test)
    y_predicted_cls = y_predicted.round()
    acc = y_predicted_cls.eq(y_test).sum() / float(y_test.shape[0])
    print(f'accuracy = {acc:.4f}')

tutorial_09_dataloader.py

import torch
import torchvision
from torch.utils.data import Dataset, DataLoader
import numpy as np
import math


class WineDataset(Dataset):
    def __init__(self):
        # data loading
        xy = np.loadtxt('./data/wine.csv', delimiter=",", dtype=np.float32, skiprows=1)
        self.x = torch.from_numpy(xy[:, 1:])
        self.y = torch.from_numpy(xy[:, [0]]) # n_samples, 1
        self.n_samples = xy.shape[0]

    def __getitem__(self, index):
        return self.x[index], self.y[index]

    def __len__(self):
        return self.n_samples

dataset = WineDataset()
first_data = dataset[0]
features, labels = first_data
print(features, labels)
print("-------------------------------------------------------------")
dataloder = DataLoader(dataset=dataset, batch_size=4, shuffle=True, num_workers=2)

dataiter = iter(dataloder)
data = dataiter.next()
features, labels = data
print(features, labels)

print("--------------------------------------------------------------")
# training loop
n_epochs = 2
total_samples = len(dataset)
n_iterations = math.ceil(total_samples/4)
print(total_samples, n_iterations)

for epoch in range(n_epochs):
    for i, (inputs, labels) in enumerate(dataloder):
        # forward, backward, update
        if (i+1) % 5 == 0:
            print(f'epoch {epoch+1}/{n_epochs}, step {i+1}/{n_iterations}, inputs {inputs.shape}')

tutorial_10_transformers.py

import torch
import torchvision
from torch.utils.data import Dataset, DataLoader
import numpy as np
import math


class WineDataset(Dataset):
    def __init__(self, transform = None):
        # data loading
        xy = np.loadtxt('./data/wine.csv', delimiter=",", dtype=np.float32, skiprows=1)
        self.n_samples = xy.shape[0]

        # note that we do not convert to tensor here
        self.x = xy[:, 0:]
        self.y = xy[:, [-1]]

        self.transform = transform

    def __getitem__(self, index):
        sample = self.x[index], self.y[index]

        if self.transform:
            sample = self.transform(sample)

        return sample


    def __len__(self):
        return self.n_samples


class ToTensor:
    def __call__(self, sample):
        inputs, targets = sample
        return torch.from_numpy(inputs), torch.from_numpy(targets)

class MulTransform:
    def __init__(self, factor):
        self.factor = factor

    def __call__(self, sample):
        inputs, target = sample
        inputs *= self.factor
        return inputs, target

dataset = WineDataset(transform=None)
first_data = dataset[0]
features, labels = first_data
print(type(features), type(labels))
print(features)

composed = torchvision.transforms.Compose([ToTensor(), MulTransform(4)])
dataset = WineDataset(transform=composed)
first_data = dataset[0]
features, labels = first_data
print(type(features), type(labels))
print(features)

tutorial_11_ce.py

import torch
import torch.nn as nn
import numpy as np

def cross_entropy(actual, predicted):
    loss = -np.sum(actual * np.log(predicted))
    return loss

# y must be one hot encoded
# if class 0: [1 0 0]
# if class 1: [0 1 0]
# if class 2: [0 0 1]

Y = np.array([1, 0, 0])

# y_pred has probabilities
Y_pred_good = np.array([0.7, 0.2, 0.1])
Y_pred_bad = np.array([0.1, 0.3, 0.6])

l1 = cross_entropy(Y, Y_pred_good)
l2 = cross_entropy(Y, Y_pred_bad)
print(f'Loss1 numpy: {l1:.4f}')
print(f'Loss2 numpy: {l2:.4f}')

print("===== Using PyTorch =====")
loss = nn.CrossEntropyLoss()

# 3 samples
Y = torch.tensor([2, 0, 1])

# nsamples x nclasses = 3x3
Y_pred_good = torch.tensor([[0.1, 1.0, 2.0], [2.0, 1.0, 0.1], [0.1, 3.0, 0.1]])
Y_pred_bad = torch.tensor([[0.5, 2.0, 0.3], [0.2, 1.0, 3.0], [2.0, 0.2, 2.0]])

l1 = loss(Y_pred_good, Y)
l2 = loss(Y_pred_bad, Y)

print(l1.item())
print(l2.item())

_, predictions1 = torch.max(Y_pred_good, 1)
_, predictions2 = torch.max(Y_pred_bad, 1)

print(predictions1)
print(predictions2)

tutorial_11_softmax_and_crossentropy.py

import torch
import torch.nn as nn
import numpy as np

def softmax(x):
    return np.exp(x) / np.sum(np.exp(x), axis = 0)

x = np.array([2.0, 1.0, 0.1])
outputs = softmax(x)
print(outputs)

x = torch.tensor([2.0, 1.0, 0.1])
outputs = torch.softmax(x, dim = 0)
print(outputs )

tutorial_12_activation_functions.py

import torch
import torch.nn as nn
import torch.nn.functional as F

# option 1 (create nn modules)
class NeuralNet(nn.Module):
    def __init__(self, input_size, hidden_size):
        super(NeuralNet, self).__init__()
        self.linear1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.linear2 = nn.Linear(hidden_size, 1)
        self.sigmoid = nn.Sigmoid()

    def forward(self, x):
        out = self.linear1(x)
        out = self.relu(out)
        out = self.linear2(out)
        out = self.sigmoid(out)
        return out

# option 2 (use activation functions directly in forward pass
class NeuralNet(nn.Module):
    def __init__(self, input_size, hidden_size):
        super(NeuralNet, self).__init__()
        self.linear1 = nn.Linear(input_size, hidden_size)
        self.linear2 = nn.Linear(hidden_size, 1)

    def forward(self, x):
        out = torch.relu(self.linear1(x))
        out = torch.sigmoid(self.linear2(out))
        return out

tutorial_13_feedforward.py

# MNIST
# DataLoader, Transformation
# Multilayer Neural Net, activation function
# Loss and Optimizer
# Training Loop (batch training)
# Model evaluation
# GPU support

import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
import matplotlib.pyplot as plt

# device config
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

# hyper parameters
input_size = 784 # 28X28
hidden_size = 100
num_classes = 10
num_epochs = 2
batch_size = 100
learning_rate = 0.001

# MNIST
train_dataset = torchvision.datasets.MNIST(root = './data', train = True, transform=transforms.ToTensor(), download=True)
test_dataset = torchvision.datasets.MNIST(root = './data', train = False, transform=transforms.ToTensor())

train_loader = torch.utils.data.DataLoader(dataset = train_dataset, batch_size = batch_size, shuffle = True)
test_loater = torch.utils.data.DataLoader(dataset = test_dataset, batch_size = batch_size)

examples = iter(train_loader)
samples, labels = examples.next()
print(samples.size(), labels.size())

for i in range(6):
    plt.subplot(2, 3, i+1)
    plt.imshow(samples[i][0], cmap = 'gray')
plt.show()

class NeuralNet(nn.Module):
    def __init__(self, input_size, hidden_size, num_classes):
        super(NeuralNet, self).__init__()
        self.l1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.l2 = nn.Linear(hidden_size, num_classes)

    def forward(self, x):
        out = self.l1(x)
        out = self.relu(out)
        out = self.l2(out)
        return out

model = NeuralNet(input_size, hidden_size, num_classes)

# loss and optimizer
criterion = nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), lr = learning_rate)

# training loop
n_total_steps = len(train_loader)
for epoch in range(num_epochs):
    for i, (images, labels) in enumerate(train_loader):
        # 100, 1, 28, 28
        # 100, 784
        images = images.reshape(-1, 28*28).to(device)
        labels = labels.to(device)

        # forward
        outputs = model(images)
        loss = criterion(outputs, labels)

        # backward
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

        if (i + 1)% 100 == 0:
            print(f'epoch {epoch+1} / {num_epochs}, step {i + 1} / {n_total_steps}, loss = {loss.item():.4f}')

# testing
with torch.no_grad():
    n_correct = 0
    n_samples = 0
    for images, labels in test_loater:
        images = images.reshape(-1, 28 * 28).to(device)
        labels = labels.to(device)
        outputs = model(images)

        # value, index
        _, predictions = torch.max(outputs, 1)
        n_samples += labels.shape[0]
        n_correct += (predictions == labels).sum().item()

    acc = 100.0 * n_correct/ n_samples
    print(f'accuracy = {acc}')

tutorial_14_cnn.py

import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import torchvision.transforms as transforms
import matplotlib.pyplot as plt
import numpy as np

# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

# Hyper-parameters
num_epochs = 5
batch_size = 4
learning_rate = 0.001

# dataset has PILImage images of range [0, 1].
# We transform them to Tensors of normalized range [-1, 1]
transform = transforms.Compose(
    [transforms.ToTensor(),
     transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])

# CIFAR10: 60000 32x32 color images in 10 classes, with 6000 images per class
train_dataset = torchvision.datasets.CIFAR10(root='./data', train=True,
                                             download=True, transform=transform)

test_dataset = torchvision.datasets.CIFAR10(root='./data', train=False,
                                            download=True, transform=transform)

train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size,
                                           shuffle=True)

test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=batch_size,
                                          shuffle=False)

classes = ('plane', 'car', 'bird', 'cat',
           'deer', 'dog', 'frog', 'horse', 'ship', 'truck')


def imshow(img):
    img = img / 2 + 0.5  # unnormalize
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1, 2, 0)))
    plt.show()


# get some random training images
dataiter = iter(train_loader)
images, labels = dataiter.next()

# show images
imshow(torchvision.utils.make_grid(images))


class ConvNet(nn.Module):
    def __init__(self):
        super(ConvNet, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        # -> n, 3, 32, 32
        x = self.pool(F.relu(self.conv1(x)))  # -> n, 6, 14, 14
        x = self.pool(F.relu(self.conv2(x)))  # -> n, 16, 5, 5
        x = x.view(-1, 16 * 5 * 5)  # -> n, 400
        x = F.relu(self.fc1(x))  # -> n, 120
        x = F.relu(self.fc2(x))  # -> n, 84
        x = self.fc3(x)  # -> n, 10
        return x


model = ConvNet().to(device)

criterion = nn.CrossEntropyLoss()
optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)

n_total_steps = len(train_loader)
for epoch in range(num_epochs):
    for i, (images, labels) in enumerate(train_loader):
        # origin shape: [4, 3, 32, 32] = 4, 3, 1024
        # input_layer: 3 input channels, 6 output channels, 5 kernel size
        images = images.to(device)
        labels = labels.to(device)

        # Forward pass
        outputs = model(images)
        loss = criterion(outputs, labels)

        # Backward and optimize
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

        if (i + 1) % 2000 == 0:
            print(f'Epoch [{epoch + 1}/{num_epochs}], Step [{i + 1}/{n_total_steps}], Loss: {loss.item():.4f}')

print('Finished Training')
PATH = './cnn.pth'
torch.save(model.state_dict(), PATH)

with torch.no_grad():
    n_correct = 0
    n_samples = 0
    n_class_correct = [0 for i in range(10)]
    n_class_samples = [0 for i in range(10)]
    for images, labels in test_loader:
        images = images.to(device)
        labels = labels.to(device)
        outputs = model(images)
        # max returns (value ,index)
        _, predicted = torch.max(outputs, 1)
        n_samples += labels.size(0)
        n_correct += (predicted == labels).sum().item()

        for i in range(batch_size):
            label = labels[i]
            pred = predicted[i]
            if (label == pred):
                n_class_correct[label] += 1
            n_class_samples[label] += 1

    acc = 100.0 * n_correct / n_samples
    print(f'Accuracy of the network: {acc} %')

    for i in range(10):
        acc = 100.0 * n_class_correct[i] / n_class_samples[i]
        print(f'Accuracy of {classes[i]}: {acc} %')

tutorial_15_transfer_learning.py

# ImageFolder
# Scheduler
# Transfer Learning

import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import os
import copy

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])

data_transforms = {
    'train': transforms.Compose([
        transforms.RandomResizedCrop(224),
        transforms.RandomHorizontalFlip(),
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
    ]),
    'val': transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
    ]),
}

# import data
data_dir = 'data/hymenoptera_data'
sets = ['train', 'val']
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in ['train', 'val']}

dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size = 4, shuffle = True, num_workers = 0) for x in ['train', 'val']}

dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes
print(class_names)

def train_model(model, criterion, optimizer, scheduler, num_epochs = 25):
    since = time.time()

    best_model_wts = copy.deepcopy(model.state_dict())
    best_acc = 0.0

    for epoch in range(num_epochs):
        print(f'Epoch {epoch}/{num_epochs-1}')
        print('-' * 10)

        # Each epoch has a training and validation phase
        for phase in ['train', 'val']:
            if phase == 'train':
                model.train() # Set model to training mode
            else:
                model.eval() # Set model to evaluate mode

            running_loss = 0.0
            running_corrects = 0

            # Iterate over data
            for inputs, labels in datasets[phase]:
                inputs = inputs.to(device)
                labels = labels.to(device)

                # forward
                # track history if only in train
                with torch.set_grad_enabled(phase == 'train'):
                    outputs = model(inputs)
                    _, preds = torch.max(outputs, 1)
                    loss = criterion(outputs, labels)

                    # backward + optimize if only in training phase
                    if phase == 'train':
                        optimizer.zero_grad()
                        labels.backward()
                        optimizer.step()

                # statistics
                running_loss += loss.item() * inputs.size(0)
                running_corrects += torch.sum(preds == labels.data)

            if phase == 'train':
                scheduler.step()

            epoch_loss = runnig_loss / datasets_size[phase]
            epoch_acc = running_corrects.double() / dataset_sizes[phase]

            print(f'{phase} Loss: {epoch_loss:.4f} Acc: {epoch_acc:.4f}')

            # deep copy of the model
            if phase == 'val' and epoch_acc > best_acc:
                best_acc = epoch_acc
                best_model_wts = copy.deepcopy(model.state_dict())

        print()

        time_elapsed = time.time() - since
        print(f'Training complete in {time_elapsed//60:.0f}m {time_elapsed%60:.0f}s')
        print(f'Best val Acc: {best_acc:4f}')

        # load best model weights
        model.load_state_dict(best_model_wts)
        return model


    model = models.resnet18(pretrained=True)
    num_ftrs = model.fc.in_features

    model.fc = nn.Linear(num_ftrs, 2)
    model.to(device)

    criterion = nn.CrossEntropyLoss()
    optimizer = optim.SGD(model.parameters(), lr = 0.001)

    # scheduler
    step_lr_scheduler = lr_scheduler.StepLR(optimizer, step_size=7, gamma=0.1)

    model = train_model(model, criterion, optimizer, scheduler, num_epochs=20)

    #####

    model = models.resnet18(pretrained=True)
    for param in model.parameters():
        param.requires_grad = False

    num_ftrs = model.fc.in_features

    model.fc = nn.Linear(num_ftrs, 2)
    model.to(device)

    criterion = nn.CrossEntropyLoss()
    optimizer = optim.SGD(model.parameters(), lr=0.001)

    # scheduler
    step_lr_scheduler = lr_scheduler.StepLR(optimizer, step_size=7, gamma=0.1)

    model = train_model(model, criterion, optimizer, scheduler, num_epochs=20)

tutorial_15_transfer_learning2.py

import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import os
import copy

mean = np.array([0.5, 0.5, 0.5])
std = np.array([0.25, 0.25, 0.25])

data_transforms = {
    'train': transforms.Compose([
        transforms.RandomResizedCrop(224),
        transforms.RandomHorizontalFlip(),
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
    ]),
    'val': transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
    ]),
}

data_dir = 'data/hymenoptera_data'
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),
                                          data_transforms[x])
                  for x in ['train', 'val']}
dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,
                                             shuffle=True, num_workers=0)
              for x in ['train', 'val']}
dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
print(class_names)


def imshow(inp, title):
    """Imshow for Tensor."""
    inp = inp.numpy().transpose((1, 2, 0))
    inp = std * inp + mean
    inp = np.clip(inp, 0, 1)
    plt.imshow(inp)
    plt.title(title)
    plt.show()


# Get a batch of training data
inputs, classes = next(iter(dataloaders['train']))

# Make a grid from batch
out = torchvision.utils.make_grid(inputs)

imshow(out, title=[class_names[x] for x in classes])

def train_model(model, criterion, optimizer, scheduler, num_epochs=25):
    since = time.time()

    best_model_wts = copy.deepcopy(model.state_dict())
    best_acc = 0.0

    for epoch in range(num_epochs):
        print('Epoch {}/{}'.format(epoch, num_epochs - 1))
        print('-' * 10)

        # Each epoch has a training and validation phase
        for phase in ['train', 'val']:
            if phase == 'train':
                model.train()  # Set model to training mode
            else:
                model.eval()   # Set model to evaluate mode

            running_loss = 0.0
            running_corrects = 0

            # Iterate over data.
            for inputs, labels in dataloaders[phase]:
                inputs = inputs.to(device)
                labels = labels.to(device)

                # forward
                # track history if only in train
                with torch.set_grad_enabled(phase == 'train'):
                    outputs = model(inputs)
                    _, preds = torch.max(outputs, 1)
                    loss = criterion(outputs, labels)

                    # backward + optimize only if in training phase
                    if phase == 'train':
                        optimizer.zero_grad()
                        loss.backward()
                        optimizer.step()

                # statistics
                running_loss += loss.item() * inputs.size(0)
                running_corrects += torch.sum(preds == labels.data)

            if phase == 'train':
                scheduler.step()

            epoch_loss = running_loss / dataset_sizes[phase]
            epoch_acc = running_corrects.double() / dataset_sizes[phase]

            print('{} Loss: {:.4f} Acc: {:.4f}'.format(
                phase, epoch_loss, epoch_acc))

            # deep copy the model
            if phase == 'val' and epoch_acc > best_acc:
                best_acc = epoch_acc
                best_model_wts = copy.deepcopy(model.state_dict())

        print()

    time_elapsed = time.time() - since
    print('Training complete in {:.0f}m {:.0f}s'.format(
        time_elapsed // 60, time_elapsed % 60))
    print('Best val Acc: {:4f}'.format(best_acc))

    # load best model weights
    model.load_state_dict(best_model_wts)
    return model


#### Finetuning the convnet ####
# Load a pretrained model and reset final fully connected layer.

model = models.resnet18(pretrained=True)
num_ftrs = model.fc.in_features
# Here the size of each output sample is set to 2.
# Alternatively, it can be generalized to nn.Linear(num_ftrs, len(class_names)).
model.fc = nn.Linear(num_ftrs, 2)

model = model.to(device)

criterion = nn.CrossEntropyLoss()

# Observe that all parameters are being optimized
optimizer = optim.SGD(model.parameters(), lr=0.001)

# StepLR Decays the learning rate of each parameter group by gamma every step_size epochs
# Decay LR by a factor of 0.1 every 7 epochs
# Learning rate scheduling should be applied after optimizer’s update
# e.g., you should write your code this way:
# for epoch in range(100):
#     train(...)
#     validate(...)
#     scheduler.step()

step_lr_scheduler = lr_scheduler.StepLR(optimizer, step_size=7, gamma=0.1)

model = train_model(model, criterion, optimizer, step_lr_scheduler, num_epochs=25)


#### ConvNet as fixed feature extractor ####
# Here, we need to freeze all the network except the final layer.
# We need to set requires_grad == False to freeze the parameters so that the gradients are not computed in backward()
model_conv = torchvision.models.resnet18(pretrained=True)
for param in model_conv.parameters():
    param.requires_grad = False

# Parameters of newly constructed modules have requires_grad=True by default
num_ftrs = model_conv.fc.in_features
model_conv.fc = nn.Linear(num_ftrs, 2)

model_conv = model_conv.to(device)

criterion = nn.CrossEntropyLoss()

# Observe that only parameters of final layer are being optimized as
# opposed to before.
optimizer_conv = optim.SGD(model_conv.fc.parameters(), lr=0.001, momentum=0.9)

# Decay LR by a factor of 0.1 every 7 epochs
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)

model_conv = train_model(model_conv, criterion, optimizer_conv,
                         exp_lr_scheduler, num_epochs=25)

tutorial_classifier.py

import torch
import torchvision
import torchvision.transforms as transforms

import matplotlib.pyplot as plt
import numpy as np

import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])

trainset = torchvision.datasets.CIFAR10(root = './data', train = True, download = True, transform = transform)
trainloader = torch.utils.data.DataLoader(trainset, batch_size = 4, shuffle = True, num_workers = 2)

testset = torchvision.datasets.CIFAR10(root = './data', train = False, download = True, transform = transform)
testloader = torch.utils.data.DataLoader(testset, batch_size = 4, shuffle = False, num_workers = 2)

classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')


# functions to show an image
def imshow(img):
	img = img / 2 + 0.5	#unnormalize
	npimg = img.numpy()
	plt.imshow(np.transpose(npimg, (1, 2, 0)))
	plt.show()

# get some random training images
dataiter = iter(trainloader)
images, labels = dataiter.next()

# show images
imshow(torchvision.utils.make_grid(images))
# printlabels
print(' '.join('%5s' % classes[labels[j]] for j in range(4)))


## define a CNN

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = self.pool(F.relu(self.conv2(x)))
        x = x.view(-1, 16 * 5 * 5)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x


net = Net()


## Define a Loss function and optimizer
criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)


## Train the network
for epoch in range(2):  # loop over the dataset multiple times

    running_loss = 0.0
    for i, data in enumerate(trainloader, 0):
        # get the inputs; data is a list of [inputs, labels]
        inputs, labels = data

        # zero the parameter gradients
        optimizer.zero_grad()

        # forward + backward + optimize
        outputs = net(inputs)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()

        # print statistics
        running_loss += loss.item()
        if i % 2000 == 1999:    # print every 2000 mini-batches
            print('[%d, %5d] loss: %.3f' %
                  (epoch + 1, i + 1, running_loss / 2000))
            running_loss = 0.0

print('Finished Training')


# lets quickly save our trained model
PATH = './cifar_net.pth'
torch.save(net.state_dict(), PATH)


## test the network on test data
dataiter = iter(testloader)
images, labels = dataiter.next()

# print images
imshow(torchvision.utils.make_grid(images))
print('GroundTruth: ', ' '.join('%5s' % classes[labels[j]] for j in range(4)))


# load the saved model
net = Net()
net.load_state_dict(torch.load(PATH))

outputs = net(images)
_, predicted = torch.max(outputs, 1)
print('Predicted: ', ' '.join('%5s' % classes[predicted[j]] for j in range(4)))


# let us see how the network performs on whole data
correct = 0
total = 0
with torch.no_grad():
    for data in testloader:
        images, labels = data
        outputs = net(images)
        _, predicted = torch.max(outputs.data, 1)
        total += labels.size(0)
        correct += (predicted == labels).sum().item()

print('Accuracy of the network on the 10000 test images: %d %%' % (100 * correct / total))


# what classes performed well and what did not
class_correct = list(0. for i in range(10))
class_total = list(0. for i in range(10))
with torch.no_grad():
    for data in testloader:
        images, labels = data
        outputs = net(images)
        _, predicted = torch.max(outputs, 1)
        c = (predicted == labels).squeeze()
        print("====================================================")
        print(c)
        for i in range(4):
            label = labels[i]
            class_correct[label] += c[i].item()
            class_total[label] += 1


for i in range(10):
    print('Accuracy of %5s : %2d %%' % (classes[i], 100 * class_correct[i] / class_total[i]))

tutorial_coco_eval.py

import json
import tempfile

import numpy as np
import copy
import time
import torch
import torch._six

from pycocotools.cocoeval import COCOeval
from pycocotools.coco import COCO
import pycocotools.mask as mask_util

from collections import defaultdict

import utils


class CocoEvaluator(object):
    def __init__(self, coco_gt, iou_types):
        assert isinstance(iou_types, (list, tuple))
        coco_gt = copy.deepcopy(coco_gt)
        self.coco_gt = coco_gt

        self.iou_types = iou_types
        self.coco_eval = {}
        for iou_type in iou_types:
            self.coco_eval[iou_type] = COCOeval(coco_gt, iouType=iou_type)

        self.img_ids = []
        self.eval_imgs = {k: [] for k in iou_types}

    def update(self, predictions):
        img_ids = list(np.unique(list(predictions.keys())))
        self.img_ids.extend(img_ids)

        for iou_type in self.iou_types:
            results = self.prepare(predictions, iou_type)
            coco_dt = loadRes(self.coco_gt, results) if results else COCO()
            coco_eval = self.coco_eval[iou_type]

            coco_eval.cocoDt = coco_dt
            coco_eval.params.imgIds = list(img_ids)
            img_ids, eval_imgs = evaluate(coco_eval)

            self.eval_imgs[iou_type].append(eval_imgs)

    def synchronize_between_processes(self):
        for iou_type in self.iou_types:
            self.eval_imgs[iou_type] = np.concatenate(self.eval_imgs[iou_type], 2)
            create_common_coco_eval(self.coco_eval[iou_type], self.img_ids, self.eval_imgs[iou_type])

    def accumulate(self):
        for coco_eval in self.coco_eval.values():
            coco_eval.accumulate()

    def summarize(self):
        for iou_type, coco_eval in self.coco_eval.items():
            print("IoU metric: {}".format(iou_type))
            coco_eval.summarize()

    def prepare(self, predictions, iou_type):
        if iou_type == "bbox":
            return self.prepare_for_coco_detection(predictions)
        elif iou_type == "segm":
            return self.prepare_for_coco_segmentation(predictions)
        elif iou_type == "keypoints":
            return self.prepare_for_coco_keypoint(predictions)
        else:
            raise ValueError("Unknown iou type {}".format(iou_type))

    def prepare_for_coco_detection(self, predictions):
        coco_results = []
        for original_id, prediction in predictions.items():
            if len(prediction) == 0:
                continue

            boxes = prediction["boxes"]
            boxes = convert_to_xywh(boxes).tolist()
            scores = prediction["scores"].tolist()
            labels = prediction["labels"].tolist()

            coco_results.extend(
                [
                    {
                        "image_id": original_id,
                        "category_id": labels[k],
                        "bbox": box,
                        "score": scores[k],
                    }
                    for k, box in enumerate(boxes)
                ]
            )
        return coco_results

    def prepare_for_coco_segmentation(self, predictions):
        coco_results = []
        for original_id, prediction in predictions.items():
            if len(prediction) == 0:
                continue

            scores = prediction["scores"]
            labels = prediction["labels"]
            masks = prediction["masks"]

            masks = masks > 0.5

            scores = prediction["scores"].tolist()
            labels = prediction["labels"].tolist()

            rles = [
                mask_util.encode(np.array(mask[0, :, :, np.newaxis], dtype=np.uint8, order="F"))[0]
                for mask in masks
            ]
            for rle in rles:
                rle["counts"] = rle["counts"].decode("utf-8")

            coco_results.extend(
                [
                    {
                        "image_id": original_id,
                        "category_id": labels[k],
                        "segmentation": rle,
                        "score": scores[k],
                    }
                    for k, rle in enumerate(rles)
                ]
            )
        return coco_results

    def prepare_for_coco_keypoint(self, predictions):
        coco_results = []
        for original_id, prediction in predictions.items():
            if len(prediction) == 0:
                continue

            boxes = prediction["boxes"]
            boxes = convert_to_xywh(boxes).tolist()
            scores = prediction["scores"].tolist()
            labels = prediction["labels"].tolist()
            keypoints = prediction["keypoints"]
            keypoints = keypoints.flatten(start_dim=1).tolist()

            coco_results.extend(
                [
                    {
                        "image_id": original_id,
                        "category_id": labels[k],
                        'keypoints': keypoint,
                        "score": scores[k],
                    }
                    for k, keypoint in enumerate(keypoints)
                ]
            )
        return coco_results


def convert_to_xywh(boxes):
    xmin, ymin, xmax, ymax = boxes.unbind(1)
    return torch.stack((xmin, ymin, xmax - xmin, ymax - ymin), dim=1)


def merge(img_ids, eval_imgs):
    all_img_ids = utils.all_gather(img_ids)
    all_eval_imgs = utils.all_gather(eval_imgs)

    merged_img_ids = []
    for p in all_img_ids:
        merged_img_ids.extend(p)

    merged_eval_imgs = []
    for p in all_eval_imgs:
        merged_eval_imgs.append(p)

    merged_img_ids = np.array(merged_img_ids)
    merged_eval_imgs = np.concatenate(merged_eval_imgs, 2)

    # keep only unique (and in sorted order) images
    merged_img_ids, idx = np.unique(merged_img_ids, return_index=True)
    merged_eval_imgs = merged_eval_imgs[..., idx]

    return merged_img_ids, merged_eval_imgs


def create_common_coco_eval(coco_eval, img_ids, eval_imgs):
    img_ids, eval_imgs = merge(img_ids, eval_imgs)
    img_ids = list(img_ids)
    eval_imgs = list(eval_imgs.flatten())

    coco_eval.evalImgs = eval_imgs
    coco_eval.params.imgIds = img_ids
    coco_eval._paramsEval = copy.deepcopy(coco_eval.params)


#################################################################
# From pycocotools, just removed the prints and fixed
# a Python3 bug about unicode not defined
#################################################################

# Ideally, pycocotools wouldn't have hard-coded prints
# so that we could avoid copy-pasting those two functions

def createIndex(self):
    # create index
    # print('creating index...')
    anns, cats, imgs = {}, {}, {}
    imgToAnns, catToImgs = defaultdict(list), defaultdict(list)
    if 'annotations' in self.dataset:
        for ann in self.dataset['annotations']:
            imgToAnns[ann['image_id']].append(ann)
            anns[ann['id']] = ann

    if 'images' in self.dataset:
        for img in self.dataset['images']:
            imgs[img['id']] = img

    if 'categories' in self.dataset:
        for cat in self.dataset['categories']:
            cats[cat['id']] = cat

    if 'annotations' in self.dataset and 'categories' in self.dataset:
        for ann in self.dataset['annotations']:
            catToImgs[ann['category_id']].append(ann['image_id'])

    # print('index created!')

    # create class members
    self.anns = anns
    self.imgToAnns = imgToAnns
    self.catToImgs = catToImgs
    self.imgs = imgs
    self.cats = cats


maskUtils = mask_util


def loadRes(self, resFile):
    """
    Load result file and return a result api object.
    :param   resFile (str)     : file name of result file
    :return: res (obj)         : result api object
    """
    res = COCO()
    res.dataset['images'] = [img for img in self.dataset['images']]

    # print('Loading and preparing results...')
    # tic = time.time()
    if isinstance(resFile, torch._six.string_classes):
        anns = json.load(open(resFile))
    elif type(resFile) == np.ndarray:
        anns = self.loadNumpyAnnotations(resFile)
    else:
        anns = resFile
    assert type(anns) == list, 'results in not an array of objects'
    annsImgIds = [ann['image_id'] for ann in anns]
    assert set(annsImgIds) == (set(annsImgIds) & set(self.getImgIds())), \
        'Results do not correspond to current coco set'
    if 'caption' in anns[0]:
        imgIds = set([img['id'] for img in res.dataset['images']]) & set([ann['image_id'] for ann in anns])
        res.dataset['images'] = [img for img in res.dataset['images'] if img['id'] in imgIds]
        for id, ann in enumerate(anns):
            ann['id'] = id + 1
    elif 'bbox' in anns[0] and not anns[0]['bbox'] == []:
        res.dataset['categories'] = copy.deepcopy(self.dataset['categories'])
        for id, ann in enumerate(anns):
            bb = ann['bbox']
            x1, x2, y1, y2 = [bb[0], bb[0] + bb[2], bb[1], bb[1] + bb[3]]
            if 'segmentation' not in ann:
                ann['segmentation'] = [[x1, y1, x1, y2, x2, y2, x2, y1]]
            ann['area'] = bb[2] * bb[3]
            ann['id'] = id + 1
            ann['iscrowd'] = 0
    elif 'segmentation' in anns[0]:
        res.dataset['categories'] = copy.deepcopy(self.dataset['categories'])
        for id, ann in enumerate(anns):
            # now only support compressed RLE format as segmentation results
            ann['area'] = maskUtils.area(ann['segmentation'])
            if 'bbox' not in ann:
                ann['bbox'] = maskUtils.toBbox(ann['segmentation'])
            ann['id'] = id + 1
            ann['iscrowd'] = 0
    elif 'keypoints' in anns[0]:
        res.dataset['categories'] = copy.deepcopy(self.dataset['categories'])
        for id, ann in enumerate(anns):
            s = ann['keypoints']
            x = s[0::3]
            y = s[1::3]
            x1, x2, y1, y2 = np.min(x), np.max(x), np.min(y), np.max(y)
            ann['area'] = (x2 - x1) * (y2 - y1)
            ann['id'] = id + 1
            ann['bbox'] = [x1, y1, x2 - x1, y2 - y1]
    # print('DONE (t={:0.2f}s)'.format(time.time()- tic))

    res.dataset['annotations'] = anns
    createIndex(res)
    return res


def evaluate(self):
    '''
    Run per image evaluation on given images and store results (a list of dict) in self.evalImgs
    :return: None
    '''
    # tic = time.time()
    # print('Running per image evaluation...')
    p = self.params
    # add backward compatibility if useSegm is specified in params
    if p.useSegm is not None:
        p.iouType = 'segm' if p.useSegm == 1 else 'bbox'
        print('useSegm (deprecated) is not None. Running {} evaluation'.format(p.iouType))
    # print('Evaluate annotation type *{}*'.format(p.iouType))
    p.imgIds = list(np.unique(p.imgIds))
    if p.useCats:
        p.catIds = list(np.unique(p.catIds))
    p.maxDets = sorted(p.maxDets)
    self.params = p

    self._prepare()
    # loop through images, area range, max detection number
    catIds = p.catIds if p.useCats else [-1]

    if p.iouType == 'segm' or p.iouType == 'bbox':
        computeIoU = self.computeIoU
    elif p.iouType == 'keypoints':
        computeIoU = self.computeOks
    self.ious = {
        (imgId, catId): computeIoU(imgId, catId)
        for imgId in p.imgIds
        for catId in catIds}

    evaluateImg = self.evaluateImg
    maxDet = p.maxDets[-1]
    evalImgs = [
        evaluateImg(imgId, catId, areaRng, maxDet)
        for catId in catIds
        for areaRng in p.areaRng
        for imgId in p.imgIds
    ]
    # this is NOT in the pycocotools code, but could be done outside
    evalImgs = np.asarray(evalImgs).reshape(len(catIds), len(p.areaRng), len(p.imgIds))
    self._paramsEval = copy.deepcopy(self.params)
    # toc = time.time()
    # print('DONE (t={:0.2f}s).'.format(toc-tic))
    return p.imgIds, evalImgs

#################################################################
# end of straight copy from pycocotools, just removing the prints
#################################################################

tutorial_coco_utils.py

import copy
import os
from PIL import Image

import torch
import torch.utils.data
import torchvision

from pycocotools import mask as coco_mask
from pycocotools.coco import COCO

import transforms as T


class FilterAndRemapCocoCategories(object):
    def __init__(self, categories, remap=True):
        self.categories = categories
        self.remap = remap

    def __call__(self, image, target):
        anno = target["annotations"]
        anno = [obj for obj in anno if obj["category_id"] in self.categories]
        if not self.remap:
            target["annotations"] = anno
            return image, target
        anno = copy.deepcopy(anno)
        for obj in anno:
            obj["category_id"] = self.categories.index(obj["category_id"])
        target["annotations"] = anno
        return image, target


def convert_coco_poly_to_mask(segmentations, height, width):
    masks = []
    for polygons in segmentations:
        rles = coco_mask.frPyObjects(polygons, height, width)
        mask = coco_mask.decode(rles)
        if len(mask.shape) < 3:
            mask = mask[..., None]
        mask = torch.as_tensor(mask, dtype=torch.uint8)
        mask = mask.any(dim=2)
        masks.append(mask)
    if masks:
        masks = torch.stack(masks, dim=0)
    else:
        masks = torch.zeros((0, height, width), dtype=torch.uint8)
    return masks


class ConvertCocoPolysToMask(object):
    def __call__(self, image, target):
        w, h = image.size

        image_id = target["image_id"]
        image_id = torch.tensor([image_id])

        anno = target["annotations"]

        anno = [obj for obj in anno if obj['iscrowd'] == 0]

        boxes = [obj["bbox"] for obj in anno]
        # guard against no boxes via resizing
        boxes = torch.as_tensor(boxes, dtype=torch.float32).reshape(-1, 4)
        boxes[:, 2:] += boxes[:, :2]
        boxes[:, 0::2].clamp_(min=0, max=w)
        boxes[:, 1::2].clamp_(min=0, max=h)

        classes = [obj["category_id"] for obj in anno]
        classes = torch.tensor(classes, dtype=torch.int64)

        segmentations = [obj["segmentation"] for obj in anno]
        masks = convert_coco_poly_to_mask(segmentations, h, w)

        keypoints = None
        if anno and "keypoints" in anno[0]:
            keypoints = [obj["keypoints"] for obj in anno]
            keypoints = torch.as_tensor(keypoints, dtype=torch.float32)
            num_keypoints = keypoints.shape[0]
            if num_keypoints:
                keypoints = keypoints.view(num_keypoints, -1, 3)

        keep = (boxes[:, 3] > boxes[:, 1]) & (boxes[:, 2] > boxes[:, 0])
        boxes = boxes[keep]
        classes = classes[keep]
        masks = masks[keep]
        if keypoints is not None:
            keypoints = keypoints[keep]

        target = {}
        target["boxes"] = boxes
        target["labels"] = classes
        target["masks"] = masks
        target["image_id"] = image_id
        if keypoints is not None:
            target["keypoints"] = keypoints

        # for conversion to coco api
        area = torch.tensor([obj["area"] for obj in anno])
        iscrowd = torch.tensor([obj["iscrowd"] for obj in anno])
        target["area"] = area
        target["iscrowd"] = iscrowd

        return image, target


def _coco_remove_images_without_annotations(dataset, cat_list=None):
    def _has_only_empty_bbox(anno):
        return all(any(o <= 1 for o in obj["bbox"][2:]) for obj in anno)

    def _count_visible_keypoints(anno):
        return sum(sum(1 for v in ann["keypoints"][2::3] if v > 0) for ann in anno)

    min_keypoints_per_image = 10

    def _has_valid_annotation(anno):
        # if it's empty, there is no annotation
        if len(anno) == 0:
            return False
        # if all boxes have close to zero area, there is no annotation
        if _has_only_empty_bbox(anno):
            return False
        # keypoints task have a slight different critera for considering
        # if an annotation is valid
        if "keypoints" not in anno[0]:
            return True
        # for keypoint detection tasks, only consider valid images those
        # containing at least min_keypoints_per_image
        if _count_visible_keypoints(anno) >= min_keypoints_per_image:
            return True
        return False

    assert isinstance(dataset, torchvision.datasets.CocoDetection)
    ids = []
    for ds_idx, img_id in enumerate(dataset.ids):
        ann_ids = dataset.coco.getAnnIds(imgIds=img_id, iscrowd=None)
        anno = dataset.coco.loadAnns(ann_ids)
        if cat_list:
            anno = [obj for obj in anno if obj["category_id"] in cat_list]
        if _has_valid_annotation(anno):
            ids.append(ds_idx)

    dataset = torch.utils.data.Subset(dataset, ids)
    return dataset


def convert_to_coco_api(ds):
    coco_ds = COCO()
    # annotation IDs need to start at 1, not 0, see torchvision issue #1530
    ann_id = 1
    dataset = {'images': [], 'categories': [], 'annotations': []}
    categories = set()
    for img_idx in range(len(ds)):
        # find better way to get target
        # targets = ds.get_annotations(img_idx)
        img, targets = ds[img_idx]
        image_id = targets["image_id"].item()
        img_dict = {}
        img_dict['id'] = image_id
        img_dict['height'] = img.shape[-2]
        img_dict['width'] = img.shape[-1]
        dataset['images'].append(img_dict)
        bboxes = targets["boxes"]
        bboxes[:, 2:] -= bboxes[:, :2]
        bboxes = bboxes.tolist()
        labels = targets['labels'].tolist()
        areas = targets['area'].tolist()
        iscrowd = targets['iscrowd'].tolist()
        if 'masks' in targets:
            masks = targets['masks']
            # make masks Fortran contiguous for coco_mask
            masks = masks.permute(0, 2, 1).contiguous().permute(0, 2, 1)
        if 'keypoints' in targets:
            keypoints = targets['keypoints']
            keypoints = keypoints.reshape(keypoints.shape[0], -1).tolist()
        num_objs = len(bboxes)
        for i in range(num_objs):
            ann = {}
            ann['image_id'] = image_id
            ann['bbox'] = bboxes[i]
            ann['category_id'] = labels[i]
            categories.add(labels[i])
            ann['area'] = areas[i]
            ann['iscrowd'] = iscrowd[i]
            ann['id'] = ann_id
            if 'masks' in targets:
                ann["segmentation"] = coco_mask.encode(masks[i].numpy())
            if 'keypoints' in targets:
                ann['keypoints'] = keypoints[i]
                ann['num_keypoints'] = sum(k != 0 for k in keypoints[i][2::3])
            dataset['annotations'].append(ann)
            ann_id += 1
    dataset['categories'] = [{'id': i} for i in sorted(categories)]
    coco_ds.dataset = dataset
    coco_ds.createIndex()
    return coco_ds


def get_coco_api_from_dataset(dataset):
    for _ in range(10):
        if isinstance(dataset, torchvision.datasets.CocoDetection):
            break
        if isinstance(dataset, torch.utils.data.Subset):
            dataset = dataset.dataset
    if isinstance(dataset, torchvision.datasets.CocoDetection):
        return dataset.coco
    return convert_to_coco_api(dataset)


class CocoDetection(torchvision.datasets.CocoDetection):
    def __init__(self, img_folder, ann_file, transforms):
        super(CocoDetection, self).__init__(img_folder, ann_file)
        self._transforms = transforms

    def __getitem__(self, idx):
        img, target = super(CocoDetection, self).__getitem__(idx)
        image_id = self.ids[idx]
        target = dict(image_id=image_id, annotations=target)
        if self._transforms is not None:
            img, target = self._transforms(img, target)
        return img, target


def get_coco(root, image_set, transforms, mode='instances'):
    anno_file_template = "{}_{}2017.json"
    PATHS = {
        "train": ("train2017", os.path.join("annotations", anno_file_template.format(mode, "train"))),
        "val": ("val2017", os.path.join("annotations", anno_file_template.format(mode, "val"))),
        # "train": ("val2017", os.path.join("annotations", anno_file_template.format(mode, "val")))
    }

    t = [ConvertCocoPolysToMask()]

    if transforms is not None:
        t.append(transforms)
    transforms = T.Compose(t)

    img_folder, ann_file = PATHS[image_set]
    img_folder = os.path.join(root, img_folder)
    ann_file = os.path.join(root, ann_file)

    dataset = CocoDetection(img_folder, ann_file, transforms=transforms)

    if image_set == "train":
        dataset = _coco_remove_images_without_annotations(dataset)

    # dataset = torch.utils.data.Subset(dataset, [i for i in range(500)])

    return dataset


def get_coco_kp(root, image_set, transforms):
    return get_coco(root, image_set, transforms, mode="person_keypoints")

tutorial_data_cifar-10-batches-py_readme.html

<meta HTTP-EQUIV="REFRESH" content="0; url=http://www.cs.toronto.edu/~kriz/cifar.html">

tutorial_data_PennFudanPed_added-object-list.txt

# image name (\t) object index
FudanPed00004.png	2
FudanPed00005.png	2
FudanPed00006.png	2
FudanPed00007.png	3
FudanPed00008.png	2
FudanPed00021.png	2
FudanPed00021.png	3
FudanPed00025.png	2
FudanPed00025.png	3
FudanPed00025.png	4
FudanPed00025.png	5
FudanPed00025.png	6
FudanPed00036.png	3
FudanPed00036.png	4
FudanPed00037.png	2
FudanPed00041.png	3
FudanPed00044.png	3
FudanPed00044.png	4
FudanPed00046.png	4
FudanPed00047.png	3
FudanPed00049.png	3
FudanPed00057.png	4
FudanPed00057.png	5
FudanPed00058.png	2
FudanPed00058.png	3
FudanPed00058.png	4
FudanPed00058.png	5
FudanPed00058.png	6
FudanPed00058.png	7
FudanPed00058.png	8
FudanPed00063.png	3
FudanPed00063.png	4
FudanPed00063.png	5
FudanPed00065.png	5
FudanPed00071.png	3
PennPed00001.png	5
PennPed00002.png	6
PennPed00005.png	5
PennPed00006.png	4
PennPed00008.png	4
PennPed00009.png	7
PennPed00010.png	5
PennPed00010.png	6
PennPed00011.png	2
PennPed00013.png	4
PennPed00014.png	4
PennPed00021.png	3
PennPed00022.png	5
PennPed00025.png	2
PennPed00025.png	3
PennPed00027.png	3
PennPed00033.png	4
PennPed00034.png	4
PennPed00035.png	3
PennPed00043.png	3
PennPed00043.png	4
PennPed00043.png	5
PennPed00044.png	4
PennPed00045.png	5
PennPed00045.png	6
PennPed00046.png	3
PennPed00047.png	3
PennPed00049.png	3
PennPed00049.png	4
PennPed00052.png	5
PennPed00055.png	2
PennPed00057.png	2
PennPed00058.png	4
PennPed00061.png	2
PennPed00062.png	3
PennPed00062.png	4
PennPed00066.png	3
PennPed00068.png	4
PennPed00071.png	5
PennPed00071.png	6
PennPed00084.png	3
PennPed00086.png	4
PennPed00086.png	5

tutorial_data_PennFudanPed_Annotation_FudanPed00001.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00001.png"
Image size (X x Y x C) : 559 x 536 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (160, 182) - (302, 431)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00001_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (420, 171) - (535, 486)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00001_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00002.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00002.png"
Image size (X x Y x C) : 455 x 414 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (68, 93) - (191, 380)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00002_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00003.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00003.png"
Image size (X x Y x C) : 479 x 445 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (293, 135) - (447, 421)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00003_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00004.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00004.png"
Image size (X x Y x C) : 396 x 397 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (168, 60) - (324, 338)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00004_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (9, 61) - (48, 180)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00004_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00005.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00005.png"
Image size (X x Y x C) : 335 x 344 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (188, 59) - (320, 336)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00005_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (2, 53) - (40, 158)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00005_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00006.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00006.png"
Image size (X x Y x C) : 385 x 426 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (208, 108) - (346, 385)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00006_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (2, 108) - (87, 384)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00006_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00007.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00007.png"
Image size (X x Y x C) : 539 x 381 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (112, 69) - (218, 346)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00007_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (378, 76) - (529, 377)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00007_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (317, 108) - (347, 192)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00007_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00008.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00008.png"
Image size (X x Y x C) : 388 x 454 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (228, 158) - (370, 436)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00008_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (39, 179) - (115, 363)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00008_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00009.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00009.png"
Image size (X x Y x C) : 465 x 441 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (306, 138) - (453, 430)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00009_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (157, 124) - (298, 398)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00009_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00010.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00010.png"
Image size (X x Y x C) : 411 x 393 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (281, 90) - (401, 374)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00010_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00011.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00011.png"
Image size (X x Y x C) : 459 x 420 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (278, 112) - (438, 394)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00011_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00012.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00012.png"
Image size (X x Y x C) : 468 x 384 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (159, 71) - (295, 361)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00012_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (328, 58) - (439, 327)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00012_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00013.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00013.png"
Image size (X x Y x C) : 652 x 498 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (389, 193) - (554, 476)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00013_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00014.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00014.png"
Image size (X x Y x C) : 456 x 383 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (234, 86) - (405, 367)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00014_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00015.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00015.png"
Image size (X x Y x C) : 336 x 349 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (19, 43) - (174, 327)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00015_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00016.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00016.png"
Image size (X x Y x C) : 544 x 425 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (80, 86) - (205, 383)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00016_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (279, 94) - (400, 361)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00016_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (411, 101) - (495, 378)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00016_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00017.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00017.png"
Image size (X x Y x C) : 266 x 342 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (115, 48) - (244, 332)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00017_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00018.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00018.png"
Image size (X x Y x C) : 253 x 323 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (20, 19) - (126, 304)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00018_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00019.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00019.png"
Image size (X x Y x C) : 497 x 442 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (7, 135) - (142, 389)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00019_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (194, 123) - (339, 421)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00019_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00020.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00020.png"
Image size (X x Y x C) : 555 x 417 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (339, 99) - (508, 381)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00020_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00021.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00021.png"
Image size (X x Y x C) : 490 x 378 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (324, 76) - (470, 367)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00021_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (234, 93) - (268, 167)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00021_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (47, 95) - (69, 160)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00021_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00022.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00022.png"
Image size (X x Y x C) : 536 x 465 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (112, 169) - (209, 449)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00022_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (397, 171) - (514, 455)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00022_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00023.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00023.png"
Image size (X x Y x C) : 376 x 378 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (202, 84) - (341, 366)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00023_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00024.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00024.png"
Image size (X x Y x C) : 479 x 378 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (103, 84) - (270, 370)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00024_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00025.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00025.png"
Image size (X x Y x C) : 425 x 369 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 6 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (226, 69) - (396, 354)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (44, 87) - (94, 256)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (128, 74) - (189, 262)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (180, 53) - (228, 255)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (213, 73) - (273, 262)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (314, 62) - (383, 266)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00025_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00026.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00026.png"
Image size (X x Y x C) : 440 x 427 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (44, 78) - (150, 389)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00026_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (185, 89) - (279, 373)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00026_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00027.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00027.png"
Image size (X x Y x C) : 302 x 363 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (104, 45) - (253, 328)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00027_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00028.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00028.png"
Image size (X x Y x C) : 317 x 345 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (7, 16) - (149, 303)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00028_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (186, 18) - (316, 321)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00028_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00029.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00029.png"
Image size (X x Y x C) : 435 x 404 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (246, 72) - (368, 351)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00029_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00030.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00030.png"
Image size (X x Y x C) : 462 x 387 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (59, 85) - (208, 375)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00030_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00031.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00031.png"
Image size (X x Y x C) : 569 x 430 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (298, 122) - (444, 408)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00031_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00032.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00032.png"
Image size (X x Y x C) : 608 x 474 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (456, 162) - (573, 453)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00032_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00033.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00033.png"
Image size (X x Y x C) : 396 x 357 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (165, 53) - (304, 346)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00033_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00034.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00034.png"
Image size (X x Y x C) : 309 x 351 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (111, 37) - (254, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00034_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00035.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00035.png"
Image size (X x Y x C) : 292 x 349 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (64, 39) - (195, 331)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00035_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00036.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00036.png"
Image size (X x Y x C) : 1017 x 444 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (131, 98) - (279, 394)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00036_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (802, 120) - (937, 381)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00036_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (244, 133) - (330, 363)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00036_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (726, 145) - (789, 345)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00036_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00037.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00037.png"
Image size (X x Y x C) : 423 x 361 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (259, 63) - (415, 349)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00037_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (190, 98) - (209, 170)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00037_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00038.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00038.png"
Image size (X x Y x C) : 422 x 346 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (219, 44) - (400, 331)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00038_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00039.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00039.png"
Image size (X x Y x C) : 493 x 487 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (137, 137) - (199, 311)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00039_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (231, 130) - (331, 410)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00039_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00040.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00040.png"
Image size (X x Y x C) : 550 x 482 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (201, 157) - (279, 437)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00040_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (279, 172) - (377, 430)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00040_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00041.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00041.png"
Image size (X x Y x C) : 552 x 507 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (351, 161) - (439, 437)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00041_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (284, 181) - (357, 439)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00041_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (42, 186) - (110, 388)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00041_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00042.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00042.png"
Image size (X x Y x C) : 588 x 547 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (159, 186) - (250, 470)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00042_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (288, 156) - (392, 449)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00042_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00043.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00043.png"
Image size (X x Y x C) : 493 x 518 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (64, 139) - (147, 426)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00043_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (156, 139) - (248, 435)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00043_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (261, 128) - (358, 431)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00043_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00044.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00044.png"
Image size (X x Y x C) : 521 x 494 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (246, 170) - (340, 462)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00044_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (337, 175) - (426, 464)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00044_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (37, 129) - (181, 492)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00044_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (436, 157) - (501, 402)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00044_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00045.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00045.png"
Image size (X x Y x C) : 487 x 538 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (198, 198) - (294, 481)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00045_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (319, 201) - (404, 499)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00045_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (395, 212) - (469, 495)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00045_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00046.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00046.png"
Image size (X x Y x C) : 567 x 438 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (178, 123) - (271, 410)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00046_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (299, 114) - (370, 335)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00046_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (446, 104) - (507, 315)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00046_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (521, 119) - (565, 258)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00046_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00047.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00047.png"
Image size (X x Y x C) : 472 x 520 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (272, 198) - (371, 482)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00047_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (31, 195) - (90, 427)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00047_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (384, 185) - (430, 298)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00047_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00048.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00048.png"
Image size (X x Y x C) : 585 x 559 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (6, 242) - (84, 535)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00048_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (79, 231) - (144, 455)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00048_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (158, 219) - (251, 507)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00048_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (460, 263) - (580, 544)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00048_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00049.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00049.png"
Image size (X x Y x C) : 447 x 512 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (127, 123) - (213, 412)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00049_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (214, 106) - (317, 392)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00049_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (315, 107) - (435, 387)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00049_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00050.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00050.png"
Image size (X x Y x C) : 580 x 516 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (33, 203) - (135, 484)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00050_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (291, 205) - (369, 412)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00050_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00051.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00051.png"
Image size (X x Y x C) : 448 x 501 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (126, 191) - (218, 476)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00051_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00052.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00052.png"
Image size (X x Y x C) : 461 x 504 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (206, 189) - (308, 492)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00052_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00053.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00053.png"
Image size (X x Y x C) : 541 x 580 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (94, 169) - (195, 432)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00053_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (389, 150) - (499, 453)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00053_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00054.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00054.png"
Image size (X x Y x C) : 533 x 498 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (97, 135) - (182, 418)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00054_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (287, 114) - (358, 332)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00054_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (364, 121) - (437, 329)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00054_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00055.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00055.png"
Image size (X x Y x C) : 390 x 555 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (148, 178) - (277, 530)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00055_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00056.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00056.png"
Image size (X x Y x C) : 565 x 581 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (439, 247) - (537, 522)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00056_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (200, 259) - (270, 529)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00056_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (252, 256) - (374, 528)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00056_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00057.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00057.png"
Image size (X x Y x C) : 482 x 519 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (22, 91) - (143, 406)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00057_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (131, 93) - (205, 358)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00057_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (237, 83) - (312, 356)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00057_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (343, 117) - (388, 267)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00057_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (386, 116) - (427, 250)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00057_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00058.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00058.png"
Image size (X x Y x C) : 522 x 479 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 8 { "PASpersonWalking" "PASpersonStanding" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (145, 92) - (261, 463)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (43, 123) - (64, 211)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (289, 102) - (341, 280)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (353, 97) - (406, 276)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (427, 126) - (446, 182)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 6 ("PASpersonStanding")
Original label for object 6 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 6 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (462, 126) - (474, 171)
Pixel mask for object 6 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 7 ("PASpersonStanding")
Original label for object 7 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 7 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (473, 133) - (489, 183)
Pixel mask for object 7 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

# Details for pedestrian 8 ("PASpersonWalking")
Original label for object 8 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 8 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (492, 121) - (517, 202)
Pixel mask for object 8 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00058_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00059.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00059.png"
Image size (X x Y x C) : 576 x 369 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (35, 54) - (135, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00059_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (159, 36) - (252, 329)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00059_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (270, 45) - (380, 328)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00059_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00060.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00060.png"
Image size (X x Y x C) : 517 x 440 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (188, 141) - (291, 427)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00060_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (293, 130) - (384, 430)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00060_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (395, 149) - (498, 427)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00060_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00061.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00061.png"
Image size (X x Y x C) : 547 x 407 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (165, 70) - (266, 353)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00061_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (343, 86) - (429, 381)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00061_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (406, 85) - (531, 387)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00061_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00062.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00062.png"
Image size (X x Y x C) : 414 x 341 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (175, 25) - (255, 321)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00062_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (291, 34) - (377, 330)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00062_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00063.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00063.png"
Image size (X x Y x C) : 486 x 359 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (29, 38) - (114, 332)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00063_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (156, 42) - (262, 329)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00063_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (312, 54) - (330, 99)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00063_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (297, 54) - (303, 73)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00063_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (305, 53) - (310, 73)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00063_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00064.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00064.png"
Image size (X x Y x C) : 546 x 420 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (141, 98) - (240, 387)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00064_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (317, 101) - (400, 395)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00064_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (400, 112) - (517, 407)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00064_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00065.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00065.png"
Image size (X x Y x C) : 504 x 411 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (29, 69) - (147, 382)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00065_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (147, 84) - (242, 385)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00065_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (234, 70) - (311, 393)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00065_mask.png"

# Details for pedestrian 4 ("PASpersonStanding")
Original label for object 4 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 4 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (342, 88) - (430, 351)
Pixel mask for object 4 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00065_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (13, 58) - (64, 183)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00065_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00066.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00066.png"
Image size (X x Y x C) : 360 x 359 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (248, 50) - (329, 351)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00066_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00067.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00067.png"
Image size (X x Y x C) : 453 x 416 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (62, 79) - (184, 375)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00067_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00068.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00068.png"
Image size (X x Y x C) : 375 x 398 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (249, 66) - (318, 361)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00068_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00069.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00069.png"
Image size (X x Y x C) : 354 x 379 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (215, 70) - (315, 363)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00069_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00070.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00070.png"
Image size (X x Y x C) : 390 x 382 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (288, 70) - (370, 364)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00070_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00071.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00071.png"
Image size (X x Y x C) : 363 x 353 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (121, 44) - (246, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00071_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (256, 37) - (339, 348)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00071_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (226, 52) - (255, 119)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00071_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00072.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00072.png"
Image size (X x Y x C) : 375 x 349 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (48, 40) - (139, 332)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00072_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00073.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00073.png"
Image size (X x Y x C) : 516 x 392 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (56, 66) - (159, 360)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00073_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (193, 59) - (289, 352)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00073_mask.png"

tutorial_data_PennFudanPed_Annotation_FudanPed00074.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00074.png"
Image size (X x Y x C) : 421 x 370 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (48, 51) - (126, 351)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00074_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (178, 61) - (256, 345)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/FudanPed00074_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00001.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00001.png"
Image size (X x Y x C) : 612 x 406 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (83, 66) - (197, 353)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00001_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (265, 75) - (355, 338)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00001_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (403, 38) - (501, 348)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00001_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (514, 65) - (610, 318)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00001_mask.png"

# Details for pedestrian 5 ("PASpersonStanding")
Original label for object 5 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 5 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (206, 25) - (266, 196)
Pixel mask for object 5 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00001_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00002.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00002.png"
Image size (X x Y x C) : 745 x 378 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 6 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (9, 84) - (97, 304)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (83, 45) - (165, 298)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (268, 84) - (370, 298)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (363, 33) - (516, 335)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (576, 75) - (713, 362)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (517, 92) - (608, 300)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00002_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00003.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00003.png"
Image size (X x Y x C) : 670 x 418 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (8, 33) - (174, 365)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00003_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (452, 64) - (531, 353)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00003_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (531, 91) - (661, 381)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00003_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00004.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00004.png"
Image size (X x Y x C) : 786 x 436 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (67, 61) - (170, 410)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00004_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (155, 91) - (253, 385)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00004_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (228, 94) - (325, 391)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00004_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (417, 101) - (516, 391)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00004_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (595, 112) - (734, 397)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00004_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00005.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00005.png"
Image size (X x Y x C) : 767 x 454 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonStanding" "PASpersonStanding" "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (68, 130) - (159, 405)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00005_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (165, 154) - (252, 410)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00005_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (263, 144) - (415, 439)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00005_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (540, 169) - (666, 440)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00005_mask.png"

# Details for pedestrian 5 ("PASpersonStanding")
Original label for object 5 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 5 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (602, 156) - (701, 396)
Pixel mask for object 5 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00005_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00006.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00006.png"
Image size (X x Y x C) : 631 x 436 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (111, 72) - (199, 412)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00006_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (231, 96) - (329, 388)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00006_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (443, 108) - (608, 435)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00006_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (3, 102) - (69, 397)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00006_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00007.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00007.png"
Image size (X x Y x C) : 570 x 412 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (42, 60) - (165, 350)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00007_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (127, 83) - (201, 359)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00007_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (187, 76) - (309, 369)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00007_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (299, 76) - (381, 400)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00007_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (426, 68) - (527, 343)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00007_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00008.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00008.png"
Image size (X x Y x C) : 452 x 403 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (47, 71) - (177, 366)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00008_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (199, 77) - (305, 329)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00008_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (256, 74) - (394, 345)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00008_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (343, 53) - (421, 278)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00008_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00009.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00009.png"
Image size (X x Y x C) : 648 x 413 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 7 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (47, 85) - (147, 292)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (163, 87) - (240, 348)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (225, 86) - (300, 307)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (316, 81) - (391, 369)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (375, 100) - (471, 351)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (470, 94) - (559, 395)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

# Details for pedestrian 7 ("PASpersonWalking")
Original label for object 7 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 7 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (533, 90) - (605, 376)
Pixel mask for object 7 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00009_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00010.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00010.png"
Image size (X x Y x C) : 750 x 495 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 6 { "PASpersonStanding" "PASpersonStanding" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (18, 59) - (103, 340)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (186, 56) - (262, 337)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (309, 141) - (437, 493)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (475, 76) - (619, 451)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (392, 58) - (485, 421)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (563, 36) - (681, 394)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00010_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00011.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00011.png"
Image size (X x Y x C) : 508 x 376 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (92, 62) - (236, 344)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00011_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (242, 52) - (301, 355)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00011_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00012.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00012.png"
Image size (X x Y x C) : 565 x 429 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (114, 122) - (212, 403)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00012_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00013.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00013.png"
Image size (X x Y x C) : 564 x 385 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (98, 79) - (210, 359)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00013_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (259, 96) - (364, 359)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00013_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (384, 81) - (498, 355)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00013_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (215, 91) - (257, 193)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00013_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00014.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00014.png"
Image size (X x Y x C) : 542 x 368 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (127, 40) - (206, 229)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00014_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (209, 69) - (312, 337)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00014_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (354, 60) - (448, 337)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00014_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (286, 41) - (353, 225)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00014_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00015.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00015.png"
Image size (X x Y x C) : 906 x 438 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (123, 98) - (280, 414)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00015_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (286, 91) - (448, 378)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00015_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (749, 94) - (834, 382)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00015_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00016.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00016.png"
Image size (X x Y x C) : 683 x 399 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (86, 51) - (146, 362)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00016_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (236, 93) - (329, 382)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00016_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (468, 66) - (579, 367)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00016_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00017.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00017.png"
Image size (X x Y x C) : 492 x 403 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (115, 50) - (204, 387)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00017_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (259, 49) - (398, 336)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00017_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00018.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00018.png"
Image size (X x Y x C) : 460 x 344 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (65, 32) - (145, 327)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00018_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (181, 69) - (262, 308)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00018_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00019.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00019.png"
Image size (X x Y x C) : 734 x 404 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 7 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (17, 78) - (106, 356)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (160, 70) - (249, 361)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (315, 60) - (390, 364)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (368, 47) - (474, 370)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (464, 75) - (539, 362)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (525, 80) - (639, 375)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

# Details for pedestrian 7 ("PASpersonWalking")
Original label for object 7 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 7 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (600, 78) - (704, 375)
Pixel mask for object 7 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00019_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00020.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00020.png"
Image size (X x Y x C) : 721 x 428 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (142, 121) - (264, 379)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00020_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (387, 76) - (516, 365)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00020_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (445, 77) - (607, 369)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00020_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00021.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00021.png"
Image size (X x Y x C) : 712 x 436 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (68, 118) - (218, 407)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00021_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (464, 81) - (588, 382)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00021_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (559, 111) - (681, 381)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00021_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00022.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00022.png"
Image size (X x Y x C) : 925 x 486 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (30, 118) - (167, 413)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00022_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (120, 149) - (257, 413)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00022_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (216, 152) - (354, 416)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00022_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (705, 129) - (839, 390)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00022_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (345, 162) - (424, 342)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00022_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00023.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00023.png"
Image size (X x Y x C) : 536 x 382 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (107, 60) - (275, 363)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00023_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00024.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00024.png"
Image size (X x Y x C) : 409 x 384 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (71, 58) - (170, 350)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00024_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00025.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00025.png"
Image size (X x Y x C) : 450 x 334 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (72, 34) - (216, 310)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00025_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (189, 151) - (276, 304)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00025_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (390, 2) - (421, 71)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00025_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00026.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00026.png"
Image size (X x Y x C) : 530 x 410 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (303, 94) - (447, 382)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00026_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (200, 120) - (291, 373)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00026_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00027.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00027.png"
Image size (X x Y x C) : 492 x 391 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (126, 93) - (218, 363)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00027_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (204, 81) - (322, 367)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00027_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (347, 89) - (463, 342)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00027_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00028.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00028.png"
Image size (X x Y x C) : 416 x 368 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (211, 50) - (325, 334)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00028_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00029.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00029.png"
Image size (X x Y x C) : 672 x 418 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (114, 65) - (214, 370)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00029_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (274, 98) - (339, 391)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00029_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (363, 102) - (466, 388)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00029_mask.png"

# Details for pedestrian 4 ("PASpersonStanding")
Original label for object 4 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 4 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (509, 103) - (585, 392)
Pixel mask for object 4 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00029_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00030.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00030.png"
Image size (X x Y x C) : 479 x 354 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (139, 37) - (253, 339)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00030_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (3, 37) - (95, 342)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00030_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (316, 43) - (448, 339)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00030_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00031.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00031.png"
Image size (X x Y x C) : 487 x 340 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (244, 42) - (390, 329)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00031_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00032.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00032.png"
Image size (X x Y x C) : 374 x 344 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (98, 50) - (203, 329)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00032_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00033.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00033.png"
Image size (X x Y x C) : 533 x 391 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (32, 37) - (126, 370)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00033_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (110, 50) - (214, 376)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00033_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (392, 70) - (519, 368)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00033_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (274, 149) - (389, 333)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00033_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00034.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00034.png"
Image size (X x Y x C) : 538 x 422 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (108, 58) - (289, 391)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00034_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (302, 63) - (405, 344)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00034_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (369, 67) - (493, 353)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00034_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (181, 63) - (278, 374)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00034_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00035.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00035.png"
Image size (X x Y x C) : 623 x 353 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (169, 30) - (275, 331)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00035_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (367, 54) - (541, 333)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00035_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (121, 33) - (208, 322)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00035_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00036.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00036.png"
Image size (X x Y x C) : 694 x 370 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (56, 62) - (164, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00036_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (514, 34) - (636, 328)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00036_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00037.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00037.png"
Image size (X x Y x C) : 366 x 318 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (229, 24) - (328, 307)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00037_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00038.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00038.png"
Image size (X x Y x C) : 436 x 353 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (232, 39) - (368, 316)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00038_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00039.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00039.png"
Image size (X x Y x C) : 495 x 373 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (326, 73) - (411, 360)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00039_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00040.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00040.png"
Image size (X x Y x C) : 406 x 342 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (203, 42) - (318, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00040_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00041.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00041.png"
Image size (X x Y x C) : 570 x 422 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (353, 99) - (467, 380)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00041_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00042.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00042.png"
Image size (X x Y x C) : 569 x 344 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (273, 37) - (379, 312)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00042_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (403, 36) - (472, 310)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00042_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00043.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00043.png"
Image size (X x Y x C) : 480 x 356 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (189, 47) - (297, 334)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00043_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (332, 63) - (434, 328)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00043_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (142, 78) - (199, 254)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00043_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (282, 78) - (328, 253)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00043_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (430, 73) - (456, 154)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00043_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00044.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00044.png"
Image size (X x Y x C) : 483 x 335 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (71, 36) - (170, 329)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00044_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (253, 63) - (336, 282)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00044_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (332, 54) - (408, 276)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00044_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (181, 76) - (225, 193)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00044_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00045.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00045.png"
Image size (X x Y x C) : 692 x 395 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 6 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (70, 64) - (193, 365)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (226, 65) - (321, 360)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (324, 67) - (436, 347)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (526, 45) - (639, 348)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (425, 67) - (485, 217)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (494, 62) - (548, 214)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00045_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00046.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00046.png"
Image size (X x Y x C) : 534 x 348 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (21, 58) - (111, 323)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00046_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (318, 22) - (420, 319)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00046_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (421, 62) - (441, 119)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00046_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00047.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00047.png"
Image size (X x Y x C) : 500 x 346 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (116, 57) - (253, 336)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00047_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (246, 33) - (381, 320)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00047_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (362, 42) - (427, 194)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00047_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00048.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00048.png"
Image size (X x Y x C) : 423 x 380 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (27, 33) - (118, 326)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00048_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (116, 35) - (198, 321)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00048_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (263, 21) - (385, 369)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00048_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00049.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00049.png"
Image size (X x Y x C) : 452 x 350 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (82, 48) - (176, 346)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00049_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (175, 45) - (253, 337)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00049_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (252, 81) - (307, 237)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00049_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (310, 77) - (368, 240)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00049_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00050.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00050.png"
Image size (X x Y x C) : 419 x 315 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (91, 41) - (196, 291)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00050_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00051.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00051.png"
Image size (X x Y x C) : 723 x 411 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (38, 52) - (203, 326)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00051_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (314, 67) - (481, 365)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00051_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (459, 34) - (587, 373)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00051_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (554, 67) - (628, 339)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00051_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00052.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00052.png"
Image size (X x Y x C) : 682 x 525 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (77, 137) - (175, 428)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00052_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (169, 181) - (294, 491)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00052_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (403, 157) - (494, 400)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00052_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (524, 83) - (613, 393)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00052_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (279, 179) - (334, 314)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00052_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00053.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00053.png"
Image size (X x Y x C) : 377 x 344 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (15, 29) - (124, 325)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00053_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (169, 27) - (266, 329)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00053_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00054.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00054.png"
Image size (X x Y x C) : 324 x 334 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (43, 22) - (128, 317)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00054_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00055.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00055.png"
Image size (X x Y x C) : 417 x 353 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (96, 51) - (208, 341)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00055_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (29, 8) - (122, 283)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00055_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00056.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00056.png"
Image size (X x Y x C) : 618 x 420 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonStanding" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (175, 106) - (271, 398)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00056_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (140, 122) - (193, 384)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00056_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (257, 98) - (306, 386)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00056_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00057.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00057.png"
Image size (X x Y x C) : 371 x 364 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (158, 64) - (261, 352)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00057_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (198, 18) - (266, 294)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00057_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00058.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00058.png"
Image size (X x Y x C) : 509 x 380 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (167, 27) - (245, 316)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00058_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (228, 31) - (307, 291)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00058_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (321, 65) - (452, 351)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00058_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (295, 22) - (374, 274)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00058_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00059.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00059.png"
Image size (X x Y x C) : 582 x 362 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (80, 44) - (177, 337)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00059_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (381, 36) - (529, 323)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00059_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00060.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00060.png"
Image size (X x Y x C) : 505 x 351 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (43, 23) - (142, 326)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00060_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (189, 21) - (283, 230)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00060_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (117, 28) - (191, 226)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00060_mask.png"

# Details for pedestrian 4 ("PASpersonStanding")
Original label for object 4 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 4 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (273, 81) - (389, 327)
Pixel mask for object 4 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00060_mask.png"

# Details for pedestrian 5 ("PASpersonStanding")
Original label for object 5 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 5 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (378, 31) - (476, 330)
Pixel mask for object 5 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00060_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00061.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00061.png"
Image size (X x Y x C) : 314 x 320 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (34, 17) - (143, 307)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00061_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (250, 57) - (275, 146)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00061_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00062.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00062.png"
Image size (X x Y x C) : 396 x 315 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (86, 15) - (184, 301)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00062_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (176, 35) - (288, 305)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00062_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (2, 46) - (57, 223)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00062_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (321, 54) - (373, 234)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00062_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00063.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00063.png"
Image size (X x Y x C) : 427 x 350 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (88, 50) - (262, 339)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00063_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00064.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00064.png"
Image size (X x Y x C) : 370 x 322 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (226, 29) - (334, 314)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00064_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00065.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00065.png"
Image size (X x Y x C) : 324 x 318 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (24, 21) - (139, 304)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00065_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00066.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00066.png"
Image size (X x Y x C) : 428 x 375 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (11, 76) - (128, 365)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00066_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (265, 33) - (398, 312)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00066_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (76, 30) - (189, 345)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00066_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00067.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00067.png"
Image size (X x Y x C) : 370 x 318 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (37, 13) - (184, 298)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00067_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00068.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00068.png"
Image size (X x Y x C) : 603 x 387 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 4 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (43, 89) - (153, 364)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00068_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (189, 56) - (283, 349)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00068_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (430, 37) - (568, 349)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00068_mask.png"

# Details for pedestrian 4 ("PASpersonStanding")
Original label for object 4 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 4 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (384, 47) - (455, 223)
Pixel mask for object 4 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00068_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00069.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00069.png"
Image size (X x Y x C) : 388 x 345 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (59, 44) - (149, 330)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00069_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (169, 40) - (269, 310)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00069_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00070.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00070.png"
Image size (X x Y x C) : 466 x 354 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (15, 24) - (122, 341)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00070_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (185, 14) - (306, 312)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00070_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00071.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00071.png"
Image size (X x Y x C) : 767 x 379 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 6 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (49, 19) - (171, 361)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (292, 44) - (386, 305)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (476, 25) - (567, 302)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (600, 13) - (716, 306)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (567, 53) - (612, 180)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

# Details for pedestrian 6 ("PASpersonWalking")
Original label for object 6 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 6 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (709, 53) - (744, 174)
Pixel mask for object 6 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00071_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00072.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00072.png"
Image size (X x Y x C) : 473 x 348 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (134, 25) - (254, 337)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00072_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (280, 52) - (431, 330)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00072_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00073.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00073.png"
Image size (X x Y x C) : 579 x 364 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (98, 38) - (191, 326)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00073_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (182, 46) - (277, 340)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00073_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (316, 51) - (413, 331)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00073_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00074.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00074.png"
Image size (X x Y x C) : 442 x 332 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (259, 31) - (422, 317)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00074_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (198, 23) - (283, 303)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00074_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (117, 48) - (223, 295)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00074_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00075.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00075.png"
Image size (X x Y x C) : 368 x 322 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (194, 23) - (335, 308)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00075_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00076.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00076.png"
Image size (X x Y x C) : 342 x 348 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (187, 29) - (320, 319)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00076_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00077.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00077.png"
Image size (X x Y x C) : 352 x 323 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (65, 27) - (181, 317)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00077_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00078.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00078.png"
Image size (X x Y x C) : 349 x 372 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (216, 59) - (320, 355)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00078_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00079.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00079.png"
Image size (X x Y x C) : 357 x 337 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (206, 25) - (324, 320)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00079_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00080.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00080.png"
Image size (X x Y x C) : 435 x 361 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (72, 47) - (175, 339)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00080_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (198, 43) - (314, 339)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00080_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (320, 44) - (422, 332)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00080_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00081.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00081.png"
Image size (X x Y x C) : 561 x 387 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (148, 85) - (240, 366)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00081_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (233, 54) - (337, 360)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00081_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (330, 75) - (455, 366)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00081_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00082.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00082.png"
Image size (X x Y x C) : 398 x 321 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (80, 22) - (229, 312)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00082_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00083.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00083.png"
Image size (X x Y x C) : 371 x 341 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (108, 32) - (249, 327)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00083_mask.png"

# Details for pedestrian 2 ("PASpersonStanding")
Original label for object 2 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 2 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (38, 22) - (124, 299)
Pixel mask for object 2 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00083_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00084.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00084.png"
Image size (X x Y x C) : 370 x 356 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonStanding" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (142, 46) - (310, 342)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00084_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (274, 21) - (362, 334)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00084_mask.png"

# Details for pedestrian 3 ("PASpersonStanding")
Original label for object 3 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 3 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (161, 95) - (208, 258)
Pixel mask for object 3 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00084_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00085.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00085.png"
Image size (X x Y x C) : 403 x 341 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (89, 27) - (200, 302)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00085_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (245, 38) - (368, 329)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00085_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00086.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00086.png"
Image size (X x Y x C) : 474 x 354 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 5 { "PASpersonStanding" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (8, 33) - (109, 253)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00086_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (208, 49) - (306, 318)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00086_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (345, 32) - (457, 325)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00086_mask.png"

# Details for pedestrian 4 ("PASpersonWalking")
Original label for object 4 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 4 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (73, 163) - (180, 353)
Pixel mask for object 4 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00086_mask.png"

# Details for pedestrian 5 ("PASpersonWalking")
Original label for object 5 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 5 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (113, 65) - (164, 197)
Pixel mask for object 5 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00086_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00087.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00087.png"
Image size (X x Y x C) : 325 x 343 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (23, 16) - (148, 322)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00087_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00088.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00088.png"
Image size (X x Y x C) : 375 x 320 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (73, 18) - (215, 312)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00088_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00089.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00089.png"
Image size (X x Y x C) : 428 x 317 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonStanding" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonStanding")
Original label for object 1 "PASpersonStanding" : "PennFudanPed"
Bounding box for object 1 "PASpersonStanding" (Xmin, Ymin) - (Xmax, Ymax) : (85, 25) - (165, 294)
Pixel mask for object 1 "PASpersonStanding" : "PennFudanPed/PedMasks/PennPed00089_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (140, 6) - (297, 309)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00089_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00090.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00090.png"
Image size (X x Y x C) : 500 x 370 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 3 { "PASpersonWalking" "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (80, 23) - (212, 358)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00090_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (43, 39) - (122, 346)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00090_mask.png"

# Details for pedestrian 3 ("PASpersonWalking")
Original label for object 3 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 3 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (206, 38) - (366, 326)
Pixel mask for object 3 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00090_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00091.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00091.png"
Image size (X x Y x C) : 372 x 324 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (212, 26) - (336, 321)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00091_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00092.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00092.png"
Image size (X x Y x C) : 600 x 447 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (106, 76) - (311, 434)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00092_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (288, 94) - (464, 390)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00092_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00093.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00093.png"
Image size (X x Y x C) : 368 x 311 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (51, 6) - (222, 302)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00093_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00094.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00094.png"
Image size (X x Y x C) : 422 x 349 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 1 { "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (122, 27) - (256, 322)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00094_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00095.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00095.png"
Image size (X x Y x C) : 512 x 375 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (193, 50) - (300, 337)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00095_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (320, 55) - (432, 335)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00095_mask.png"

tutorial_data_PennFudanPed_Annotation_PennPed00096.txt

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/PennPed00096.png"
Image size (X x Y x C) : 294 x 331 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (6, 38) - (103, 324)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00096_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (101, 26) - (206, 323)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/PennPed00096_mask.png"

tutorial_data_PennFudanPed_readme.txt

1. Directory structure:

PNGImages:   All the database images in PNG format.

PedMasks :   Mask for each image, also in PNG format. Pixels are labeled 0 for background, or > 0 corresponding
to a particular pedestrian ID.

Annotation:  Annotation information for each image.  Each file is in the following format (take FudanPed00001.txt as an example):

# Compatible with PASCAL Annotation Version 1.00
Image filename : "PennFudanPed/PNGImages/FudanPed00001.png"
Image size (X x Y x C) : 559 x 536 x 3
Database : "The Penn-Fudan-Pedestrian Database"
Objects with ground truth : 2 { "PASpersonWalking" "PASpersonWalking" }
# Note there may be some objects not included in the ground truth list for they are severe-occluded
# or have very small size.
# Top left pixel co-ordinates : (1, 1)
# Details for pedestrian 1 ("PASpersonWalking")
Original label for object 1 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 1 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (160, 182) - (302, 431)
Pixel mask for object 1 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00001_mask.png"

# Details for pedestrian 2 ("PASpersonWalking")
Original label for object 2 "PASpersonWalking" : "PennFudanPed"
Bounding box for object 2 "PASpersonWalking" (Xmin, Ymin) - (Xmax, Ymax) : (420, 171) - (535, 486)
Pixel mask for object 2 "PASpersonWalking" : "PennFudanPed/PedMasks/FudanPed00001_mask.png"

2. Notice
   In [1], we did not label very small, highly occluded pedestrians. 
However in this release of the dataset, we have labeled these pedestrians for future detection.
We list the newly-labeled pedestrians in the file "added-object-list.txt".

   Please download PASCAL toolkit (http://www.pascal-network.org/challenges/VOC/PAScode.tar.gz) to view the annotated pedestrians.
   
3. Acknowledgement

This material is presented to ensure timely dissemination of scholarly and technical work.
Copyright and all rights therein are retained by authors or by other copyright holders. 
 All persons copying this information are expected to adhere to the terms and constraints invoked by 
 each author's copyright. In most cases, these works may not be reposted without 
 the explicit permission of the copyright holder.

4. Related publication
[1] Object Detection Combining Recognition and Segmentation. Liming Wang, Jianbo Shi, Gang Song, I-fan Shen. To Appear in Eighth Asian Conference on Computer Vision(ACCV) 2007

tutorial_data_wine.csv

tutorial_engine.py

import math
import sys
import time
import torch

import torchvision.models.detection.mask_rcnn

from coco_utils import get_coco_api_from_dataset
from coco_eval import CocoEvaluator
import utils


def train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq):
    model.train()
    metric_logger = utils.MetricLogger(delimiter="  ")
    metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value:.6f}'))
    header = 'Epoch: [{}]'.format(epoch)

    lr_scheduler = None
    if epoch == 0:
        warmup_factor = 1. / 1000
        warmup_iters = min(1000, len(data_loader) - 1)

        lr_scheduler = utils.warmup_lr_scheduler(optimizer, warmup_iters, warmup_factor)

    for images, targets in metric_logger.log_every(data_loader, print_freq, header):
        images = list(image.to(device) for image in images)
        targets = [{k: v.to(device) for k, v in t.items()} for t in targets]

        loss_dict = model(images, targets)

        losses = sum(loss for loss in loss_dict.values())

        # reduce losses over all GPUs for logging purposes
        loss_dict_reduced = utils.reduce_dict(loss_dict)
        losses_reduced = sum(loss for loss in loss_dict_reduced.values())

        loss_value = losses_reduced.item()

        if not math.isfinite(loss_value):
            print("Loss is {}, stopping training".format(loss_value))
            print(loss_dict_reduced)
            sys.exit(1)

        optimizer.zero_grad()
        losses.backward()
        optimizer.step()

        if lr_scheduler is not None:
            lr_scheduler.step()

        metric_logger.update(loss=losses_reduced, **loss_dict_reduced)
        metric_logger.update(lr=optimizer.param_groups[0]["lr"])

    return metric_logger


def _get_iou_types(model):
    model_without_ddp = model
    if isinstance(model, torch.nn.parallel.DistributedDataParallel):
        model_without_ddp = model.module
    iou_types = ["bbox"]
    if isinstance(model_without_ddp, torchvision.models.detection.MaskRCNN):
        iou_types.append("segm")
    if isinstance(model_without_ddp, torchvision.models.detection.KeypointRCNN):
        iou_types.append("keypoints")
    return iou_types


@torch.no_grad()
def evaluate(model, data_loader, device):
    n_threads = torch.get_num_threads()
    # FIXME remove this and make paste_masks_in_image run on the GPU
    torch.set_num_threads(1)
    cpu_device = torch.device("cpu")
    model.eval()
    metric_logger = utils.MetricLogger(delimiter="  ")
    header = 'Test:'

    coco = get_coco_api_from_dataset(data_loader.dataset)
    iou_types = _get_iou_types(model)
    coco_evaluator = CocoEvaluator(coco, iou_types)

    for images, targets in metric_logger.log_every(data_loader, 100, header):
        images = list(img.to(device) for img in images)
        targets = [{k: v.to(device) for k, v in t.items()} for t in targets]

        torch.cuda.synchronize()
        model_time = time.time()
        outputs = model(images)

        outputs = [{k: v.to(cpu_device) for k, v in t.items()} for t in outputs]
        model_time = time.time() - model_time

        res = {target["image_id"].item(): output for target, output in zip(targets, outputs)}
        evaluator_time = time.time()
        coco_evaluator.update(res)
        evaluator_time = time.time() - evaluator_time
        metric_logger.update(model_time=model_time, evaluator_time=evaluator_time)

    # gather the stats from all processes
    metric_logger.synchronize_between_processes()
    print("Averaged stats:", metric_logger)
    coco_evaluator.synchronize_between_processes()

    # accumulate predictions from all images
    coco_evaluator.accumulate()
    coco_evaluator.summarize()
    torch.set_num_threads(n_threads)
    return coco_evaluator

tutorial_network.py

import torch
import torch.nn as nn
import torch.nn.functional as F

class Net(nn.Module):
	def __init__(self):
		super(Net, self).__init__()
		# 1 input image channel, 6 output channels, 3x3 square convolution kernel
		self.conv1 = nn.Conv2d(1, 6, 3)
		self.conv2 = nn.Conv2d(6, 16, 3)
		# an affine operation: y = Wx + b
		self.fc1 = nn.Linear(16*6*6, 120)	# 6*6 from image dimension
		self.fc2 = nn.Linear(120, 84)
		self.fc3 = nn.Linear(84, 10)
	
	def forward(self, x):
		# Max pooling over a (2, 2) window
		x = F.max_pool2d(F.relu(self.conv1(x)), (2, 2))
		# If the size is sqaure you can only specify a single number
		x = F.max_pool2d(F.relu(self.conv2(x)), 2)
		x = x.view(-1, self.num_flat_features(x))
		x = F.relu(self.fc1(x))
		x = F.relu(self.fc2(x))
		x = self.fc3(x)
		return x
	
	def num_flat_features(self, x):
		print('dinchak')	
		print(x.shape)
		size = x.size()[1:]	# all dimensions except the batch dimension
		num_features = 1
		for s in size:
			num_features *= s
		return num_features

net = Net()
print(net)
params = list(net.parameters())
print(len(params))
print(params[0].size())

input = torch.randn(1, 1, 32, 32)
out = net(input)
print(out)
		
#net.zero_grad()
#out.backward(torch.randn(1, 10))

output = net(input)
target = torch.randn(10) # a dummy target for eaxample
target = target.view(1, -1) # make it the same shape as output
criterion = nn.MSELoss()

loss = criterion(out, target)
print("Loss:", loss)


print(loss.grad_fn)	# MSELoss
print(loss.grad_fn.next_functions[0][0])	# Linear
print(loss.grad_fn.next_functions[0][0].next_functions[0][0])	# Relu


# backprop
net.zero_grad()	# zeros the gradient buffers of all parameters

print('conv1.bias.grad before backward')
print(net.conv1.bias.grad)

loss.backward()

print('conv1.bias.grad after backward')
print(net.conv1.bias.grad)

tutorial_nn_tutorial.ipynb

tutorial_numpy_nn.py

# -*- coding: utf-8 -*-
import numpy as np

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random input and output data
x = np.random.randn(N, D_in)
y = np.random.randn(N, D_out)

# Randomly initialize weights
w1 = np.random.randn(D_in, H)
w2 = np.random.randn(H, D_out)

learning_rate = 1e-6
for t in range(500):
    # Forward pass: compute predicted y
    h = x.dot(w1)
    h_relu = np.maximum(h, 0)
    y_pred = h_relu.dot(w2)

    # Compute and print loss
    loss = np.square(y_pred - y).sum()
    print(t, loss)

    # Backprop to compute gradients of w1 and w2 with respect to loss
    grad_y_pred = 2.0 * (y_pred - y)
    grad_w2 = h_relu.T.dot(grad_y_pred)
    grad_h_relu = grad_y_pred.dot(w2.T)
    grad_h = grad_h_relu.copy()
    grad_h[h < 0] = 0
    grad_w1 = x.T.dot(grad_h)

    # Update weights
    w1 -= learning_rate * grad_w1
    w2 -= learning_rate * grad_w2

tutorial_runs_fashion_mnist_experiment_1_00000_default_metadata.tsv

Coat
Bag
Shirt
Trouser
Sandal
Trouser
Sandal
Pullover
Sandal
Bag
Sandal
Dress
T-shirt/top
Trouser
Coat
Pullover
Coat
Sneaker
Trouser
Sandal
Trouser
Trouser
Sneaker
Bag
Dress
Dress
Trouser
Sandal
Coat
Ankle Boot
Dress
Pullover
Sandal
Dress
T-shirt/top
Sandal
T-shirt/top
Coat
T-shirt/top
Bag
Ankle Boot
T-shirt/top
Dress
Bag
Sneaker
Sneaker
Shirt
Trouser
Sneaker
Dress
Shirt
Trouser
Sneaker
Ankle Boot
T-shirt/top
T-shirt/top
Pullover
Shirt
Coat
Trouser
T-shirt/top
T-shirt/top
Sandal
Shirt
Shirt
Sandal
Sneaker
Trouser
Dress
Bag
Trouser
Dress
Dress
Ankle Boot
T-shirt/top
Sneaker
Ankle Boot
Shirt
Ankle Boot
Shirt
Bag
Sandal
Shirt
Bag
Ankle Boot
Dress
Sneaker
Trouser
Coat
Trouser
Bag
Ankle Boot
Pullover
T-shirt/top
Trouser
Pullover
Shirt
Bag
Sandal
Ankle Boot

tutorial_runs_fashion_mnist_experiment_1_00000_default_tensors.tsv

tutorial_runs_fashion_mnist_experiment_1_projector_config.pbtxt

embeddings {
  tensor_name: "default:00000"
  metadata_path: "00000/default/metadata.tsv"
  sprite {
    image_path: "00000/default/sprite.png"
    single_image_dim: 28
    single_image_dim: 28
  }
  tensor_path: "00000/default/tensors.tsv"
}

tutorial_tensor_nn.py

# -*- coding: utf-8 -*-

import torch


dtype = torch.float
device = torch.device("cpu")
# device = torch.device("cuda:0") # Uncomment this to run on GPU

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random input and output data
x = torch.randn(N, D_in, device=device, dtype=dtype)
y = torch.randn(N, D_out, device=device, dtype=dtype)

# Randomly initialize weights
w1 = torch.randn(D_in, H, device=device, dtype=dtype)
w2 = torch.randn(H, D_out, device=device, dtype=dtype)

learning_rate = 1e-6
for t in range(500):
    # Forward pass: compute predicted y
    h = x.mm(w1)
    h_relu = h.clamp(min=0)
    y_pred = h_relu.mm(w2)

    # Compute and print loss
    loss = (y_pred - y).pow(2).sum().item()
    if t % 100 == 99:
        print(t, loss)

    # Backprop to compute gradients of w1 and w2 with respect to loss
    grad_y_pred = 2.0 * (y_pred - y)
    grad_w2 = h_relu.t().mm(grad_y_pred)
    grad_h_relu = grad_y_pred.mm(w2.t())
    grad_h = grad_h_relu.clone()
    grad_h[h < 0] = 0
    grad_w1 = x.t().mm(grad_h)

    # Update weights using gradient descent
    w1 -= learning_rate * grad_w1
    w2 -= learning_rate * grad_w2

tutorial_tensorflow_static_graphs.py

import tensorflow as tf
import numpy as np

# First we set up the computational graph:

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create placeholders for the input and target data; these will be filled
# with real data when we execute the graph.
x = tf.placeholder(tf.float32, shape=(None, D_in))
y = tf.placeholder(tf.float32, shape=(None, D_out))

# Create Variables for the weights and initialize them with random data.
# A TensorFlow Variable persists its value across executions of the graph.
w1 = tf.Variable(tf.random_normal((D_in, H)))
w2 = tf.Variable(tf.random_normal((H, D_out)))

# Forward pass: Compute the predicted y using operations on TensorFlow Tensors.
# Note that this code does not actually perform any numeric operations; it
# merely sets up the computational graph that we will later execute.
h = tf.matmul(x, w1)
h_relu = tf.maximum(h, tf.zeros(1))
y_pred = tf.matmul(h_relu, w2)

# Compute loss using operations on TensorFlow Tensors
loss = tf.reduce_sum((y - y_pred) ** 2.0)

# Compute gradient of the loss with respect to w1 and w2.
grad_w1, grad_w2 = tf.gradients(loss, [w1, w2])

# Update the weights using gradient descent. To actually update the weights
# we need to evaluate new_w1 and new_w2 when executing the graph. Note that
# in TensorFlow the the act of updating the value of the weights is part of
# the computational graph; in PyTorch this happens outside the computational
# graph.
learning_rate = 1e-6
new_w1 = w1.assign(w1 - learning_rate * grad_w1)
new_w2 = w2.assign(w2 - learning_rate * grad_w2)

# Now we have built our computational graph, so we enter a TensorFlow session to
# actually execute the graph.
with tf.Session() as sess:
    # Run the graph once to initialize the Variables w1 and w2.
    sess.run(tf.global_variables_initializer())

    # Create numpy arrays holding the actual data for the inputs x and targets
    # y
    x_value = np.random.randn(N, D_in)
    y_value = np.random.randn(N, D_out)
    for t in range(500):
        # Execute the graph many times. Each time it executes we want to bind
        # x_value to x and y_value to y, specified with the feed_dict argument.
        # Each time we execute the graph we want to compute the values for loss,
        # new_w1, and new_w2; the values of these Tensors are returned as numpy
        # arrays.
        loss_value, _, _ = sess.run([loss, new_w1, new_w2],
                                    feed_dict={x: x_value, y: y_value})
        if t % 100 == 99:
            print(t+1, loss_value)

tutorial_torch_autograd.py

# -*- coding: utf-8 -*-
import torch

dtype = torch.float
device = torch.device("cpu")
# device = torch.device("cuda:0") # Uncomment this to run on GPU

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold input and outputs.
# Setting requires_grad=False indicates that we do not need to compute gradients
# with respect to these Tensors during the backward pass.
x = torch.randn(N, D_in, device=device, dtype=dtype)
y = torch.randn(N, D_out, device=device, dtype=dtype)

# Create random Tensors for weights.
# Setting requires_grad=True indicates that we want to compute gradients with
# respect to these Tensors during the backward pass.
w1 = torch.randn(D_in, H, device=device, dtype=dtype, requires_grad=True)
w2 = torch.randn(H, D_out, device=device, dtype=dtype, requires_grad=True)

learning_rate = 1e-6
for t in range(500):
    # Forward pass: compute predicted y using operations on Tensors; these
    # are exactly the same operations we used to compute the forward pass using
    # Tensors, but we do not need to keep references to intermediate values since
    # we are not implementing the backward pass by hand.
    y_pred = x.mm(w1).clamp(min=0).mm(w2)

    # Compute and print loss using operations on Tensors.
    # Now loss is a Tensor of shape (1,)
    # loss.item() gets the scalar value held in the loss.
    loss = (y_pred - y).pow(2).sum()
    if t % 100 == 99:
        print(t+1, loss.item())

    # Use autograd to compute the backward pass. This call will compute the
    # gradient of loss with respect to all Tensors with requires_grad=True.
    # After this call w1.grad and w2.grad will be Tensors holding the gradient
    # of the loss with respect to w1 and w2 respectively.
    loss.backward()

    # Manually update weights using gradient descent. Wrap in torch.no_grad()
    # because weights have requires_grad=True, but we don't need to track this
    # in autograd.
    # An alternative way is to operate on weight.data and weight.grad.data.
    # Recall that tensor.data gives a tensor that shares the storage with
    # tensor, but doesn't track history.
    # You can also use torch.optim.SGD to achieve this.
    with torch.no_grad():
        w1 -= learning_rate * w1.grad
        w2 -= learning_rate * w2.grad

        # Manually zero the gradients after updating weights
        w1.grad.zero_()
        w2.grad.zero_()

tutorial_torch_custom_autograd.py

# -*- coding: utf-8 -*-
import torch


class MyReLU(torch.autograd.Function):
    """
    We can implement our own custom autograd Functions by subclassing
    torch.autograd.Function and implementing the forward and backward passes
    which operate on Tensors.
    """

    @staticmethod
    def forward(ctx, input):
        """
        In the forward pass we receive a Tensor containing the input and return
        a Tensor containing the output. ctx is a context object that can be used
        to stash information for backward computation. You can cache arbitrary
        objects for use in the backward pass using the ctx.save_for_backward method.
        """
        print("Cutom forward function")
        ctx.save_for_backward(input)
        return input.clamp(min=0)

    @staticmethod
    def backward(ctx, grad_output):
        """
        In the backward pass we receive a Tensor containing the gradient of the loss
        with respect to the output, and we need to compute the gradient of the loss
        with respect to the input.
        """
        print("Cutom backward function")
        input, = ctx.saved_tensors
        grad_input = grad_output.clone()
        grad_input[input < 0] = 0
        return grad_input


dtype = torch.float
device = torch.device("cpu")
# device = torch.device("cuda:0") # Uncomment this to run on GPU

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold input and outputs.
x = torch.randn(N, D_in, device=device, dtype=dtype)
y = torch.randn(N, D_out, device=device, dtype=dtype)

# Create random Tensors for weights.
w1 = torch.randn(D_in, H, device=device, dtype=dtype, requires_grad=True)
w2 = torch.randn(H, D_out, device=device, dtype=dtype, requires_grad=True)

learning_rate = 1e-6
for t in range(500):
    # To apply our Function, we use Function.apply method. We alias this as 'relu'.
    relu = MyReLU.apply

    # Forward pass: compute predicted y using operations; we compute
    # ReLU using our custom autograd operation.
    y_pred = relu(x.mm(w1)).mm(w2)

    # Compute and print loss
    loss = (y_pred - y).pow(2).sum()
    if t % 100 == 99:
        print(t+1, loss.item())

    # Use autograd to compute the backward pass.
    loss.backward()

    # Update weights using gradient descent
    with torch.no_grad():
        w1 -= learning_rate * w1.grad
        w2 -= learning_rate * w2.grad

        # Manually zero the gradients after updating weights
        w1.grad.zero_()
        w2.grad.zero_()

tutorial_torch_custom_nn.py

# -*- coding: utf-8 -*-
import torch


class TwoLayerNet(torch.nn.Module):
    def __init__(self, D_in, H, D_out):
        """
        In the constructor we instantiate two nn.Linear modules and assign them as
        member variables.
        """
        super(TwoLayerNet, self).__init__()
        self.linear1 = torch.nn.Linear(D_in, H)
        self.linear2 = torch.nn.Linear(H, D_out)

    def forward(self, x):
        """
        In the forward function we accept a Tensor of input data and we must return
        a Tensor of output data. We can use Modules defined in the constructor as
        well as arbitrary operators on Tensors.
        """
        h_relu = self.linear1(x).clamp(min=0)
        y_pred = self.linear2(h_relu)
        return y_pred


# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold inputs and outputs
x = torch.randn(N, D_in)
y = torch.randn(N, D_out)

# Construct our model by instantiating the class defined above
model = TwoLayerNet(D_in, H, D_out)

# Construct our loss function and an Optimizer. The call to model.parameters()
# in the SGD constructor will contain the learnable parameters of the two
# nn.Linear modules which are members of the model.
criterion = torch.nn.MSELoss(reduction='sum')
optimizer = torch.optim.SGD(model.parameters(), lr=1e-4)
for t in range(500):
    # Forward pass: Compute predicted y by passing x to the model
    y_pred = model(x)

    # Compute and print loss
    loss = criterion(y_pred, y)
    if t % 100 == 99:
        print(t+1, loss.item())

    # Zero gradients, perform a backward pass, and update the weights.
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()

tutorial_torch_flowcontrol_weightsharing.py

# -*- coding: utf-8 -*-
import random
import torch


class DynamicNet(torch.nn.Module):
    def __init__(self, D_in, H, D_out):
        """
        In the constructor we construct three nn.Linear instances that we will use
        in the forward pass.
        """
        super(DynamicNet, self).__init__()
        self.input_linear = torch.nn.Linear(D_in, H)
        self.middle_linear = torch.nn.Linear(H, H)
        self.output_linear = torch.nn.Linear(H, D_out)

    def forward(self, x):
        """
        For the forward pass of the model, we randomly choose either 0, 1, 2, or 3
        and reuse the middle_linear Module that many times to compute hidden layer
        representations.

        Since each forward pass builds a dynamic computation graph, we can use normal
        Python control-flow operators like loops or conditional statements when
        defining the forward pass of the model.

        Here we also see that it is perfectly safe to reuse the same Module many
        times when defining a computational graph. This is a big improvement from Lua
        Torch, where each Module could be used only once.
        """
        h_relu = self.input_linear(x).clamp(min=0)
        for _ in range(random.randint(0, 3)):
            h_relu = self.middle_linear(h_relu).clamp(min=0)
        y_pred = self.output_linear(h_relu)
        return y_pred


# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold inputs and outputs
x = torch.randn(N, D_in)
y = torch.randn(N, D_out)

# Construct our model by instantiating the class defined above
model = DynamicNet(D_in, H, D_out)

# Construct our loss function and an Optimizer. Training this strange model with
# vanilla stochastic gradient descent is tough, so we use momentum
criterion = torch.nn.MSELoss(reduction='sum')
optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
for t in range(500):
    # Forward pass: Compute predicted y by passing x to the model
    y_pred = model(x)

    # Compute and print loss
    loss = criterion(y_pred, y)
    if t % 100 == 99:
        print(t+1, loss.item())

    # Zero gradients, perform a backward pass, and update the weights.
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()

tutorial_torch_nn2.py

# -*- coding: utf-8 -*-
import torch

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold inputs and outputs
x = torch.randn(N, D_in)
y = torch.randn(N, D_out)

# Use the nn package to define our model as a sequence of layers. nn.Sequential
# is a Module which contains other Modules, and applies them in sequence to
# produce its output. Each Linear Module computes output from input using a
# linear function, and holds internal Tensors for its weight and bias.
model = torch.nn.Sequential(
    torch.nn.Linear(D_in, H),
    torch.nn.ReLU(),
    torch.nn.Linear(H, D_out),
)

# The nn package also contains definitions of popular loss functions; in this
# case we will use Mean Squared Error (MSE) as our loss function.
loss_fn = torch.nn.MSELoss(reduction='sum')

learning_rate = 1e-4
for t in range(500):
    # Forward pass: compute predicted y by passing x to the model. Module objects
    # override the __call__ operator so you can call them like functions. When
    # doing so you pass a Tensor of input data to the Module and it produces
    # a Tensor of output data.
    y_pred = model(x)

    # Compute and print loss. We pass Tensors containing the predicted and true
    # values of y, and the loss function returns a Tensor containing the
    # loss.
    loss = loss_fn(y_pred, y)
    if t % 100 == 99:
        print(t+1, loss.item())

    # Zero the gradients before running the backward pass.
    model.zero_grad()

    # Backward pass: compute gradient of the loss with respect to all the learnable
    # parameters of the model. Internally, the parameters of each Module are stored
    # in Tensors with requires_grad=True, so this call will compute gradients for
    # all learnable parameters in the model.
    loss.backward()

    # Update the weights using gradient descent. Each parameter is a Tensor, so
    # we can access its gradients like we did before.
    with torch.no_grad():
        for param in model.parameters():
            param -= learning_rate * param.grad

tutorial_torch_object_detection.ipynb

tutorial_torch_optim.py

# -*- coding: utf-8 -*-
import torch

# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10

# Create random Tensors to hold inputs and outputs
x = torch.randn(N, D_in)
y = torch.randn(N, D_out)

# Use the nn package to define our model and loss function.
model = torch.nn.Sequential(
    torch.nn.Linear(D_in, H),
    torch.nn.ReLU(),
    torch.nn.Linear(H, D_out),
)
loss_fn = torch.nn.MSELoss(reduction='sum')

# Use the optim package to define an Optimizer that will update the weights of
# the model for us. Here we will use Adam; the optim package contains many other
# optimization algorithms. The first argument to the Adam constructor tells the
# optimizer which Tensors it should update.
learning_rate = 1e-4
optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)
for t in range(500):
    # Forward pass: compute predicted y by passing x to the model.
    y_pred = model(x)

    # Compute and print loss.
    loss = loss_fn(y_pred, y)
    if t % 100 == 99:
        print(t+1, loss.item())

    # Before the backward pass, use the optimizer object to zero all of the
    # gradients for the variables it will update (which are the learnable
    # weights of the model). This is because by default, gradients are
    # accumulated in buffers( i.e, not overwritten) whenever .backward()
    # is called. Checkout docs of torch.autograd.backward for more details.
    optimizer.zero_grad()

    # Backward pass: compute gradient of the loss with respect to model
    # parameters
    loss.backward()

    # Calling the step function on an Optimizer makes an update to its
    # parameters
    optimizer.step()

tutorial_torch_tensorboard.ipynb

tutorial_torch_transferlearning.ipynb

tutorial_transforms.py

import random
import torch

from torchvision.transforms import functional as F


def _flip_coco_person_keypoints(kps, width):
    flip_inds = [0, 2, 1, 4, 3, 6, 5, 8, 7, 10, 9, 12, 11, 14, 13, 16, 15]
    flipped_data = kps[:, flip_inds]
    flipped_data[..., 0] = width - flipped_data[..., 0]
    # Maintain COCO convention that if visibility == 0, then x, y = 0
    inds = flipped_data[..., 2] == 0
    flipped_data[inds] = 0
    return flipped_data


class Compose(object):
    def __init__(self, transforms):
        self.transforms = transforms

    def __call__(self, image, target):
        for t in self.transforms:
            image, target = t(image, target)
        return image, target


class RandomHorizontalFlip(object):
    def __init__(self, prob):
        self.prob = prob

    def __call__(self, image, target):
        if random.random() < self.prob:
            height, width = image.shape[-2:]
            image = image.flip(-1)
            bbox = target["boxes"]
            bbox[:, [0, 2]] = width - bbox[:, [2, 0]]
            target["boxes"] = bbox
            if "masks" in target:
                target["masks"] = target["masks"].flip(-1)
            if "keypoints" in target:
                keypoints = target["keypoints"]
                keypoints = _flip_coco_person_keypoints(keypoints, width)
                target["keypoints"] = keypoints
        return image, target


class ToTensor(object):
    def __call__(self, image, target):
        image = F.to_tensor(image)
        return image, target

tutorial_utils.py

from collections import defaultdict, deque
import datetime
import pickle
import time

import torch
import torch.distributed as dist

import errno
import os


class SmoothedValue(object):
    """Track a series of values and provide access to smoothed values over a
    window or the global series average.
    """

    def __init__(self, window_size=20, fmt=None):
        if fmt is None:
            fmt = "{median:.4f} ({global_avg:.4f})"
        self.deque = deque(maxlen=window_size)
        self.total = 0.0
        self.count = 0
        self.fmt = fmt

    def update(self, value, n=1):
        self.deque.append(value)
        self.count += n
        self.total += value * n

    def synchronize_between_processes(self):
        """
        Warning: does not synchronize the deque!
        """
        if not is_dist_avail_and_initialized():
            return
        t = torch.tensor([self.count, self.total], dtype=torch.float64, device='cuda')
        dist.barrier()
        dist.all_reduce(t)
        t = t.tolist()
        self.count = int(t[0])
        self.total = t[1]

    @property
    def median(self):
        d = torch.tensor(list(self.deque))
        return d.median().item()

    @property
    def avg(self):
        d = torch.tensor(list(self.deque), dtype=torch.float32)
        return d.mean().item()

    @property
    def global_avg(self):
        return self.total / self.count

    @property
    def max(self):
        return max(self.deque)

    @property
    def value(self):
        return self.deque[-1]

    def __str__(self):
        return self.fmt.format(
            median=self.median,
            avg=self.avg,
            global_avg=self.global_avg,
            max=self.max,
            value=self.value)


def all_gather(data):
    """
    Run all_gather on arbitrary picklable data (not necessarily tensors)
    Args:
        data: any picklable object
    Returns:
        list[data]: list of data gathered from each rank
    """
    world_size = get_world_size()
    if world_size == 1:
        return [data]

    # serialized to a Tensor
    buffer = pickle.dumps(data)
    storage = torch.ByteStorage.from_buffer(buffer)
    tensor = torch.ByteTensor(storage).to("cuda")

    # obtain Tensor size of each rank
    local_size = torch.tensor([tensor.numel()], device="cuda")
    size_list = [torch.tensor([0], device="cuda") for _ in range(world_size)]
    dist.all_gather(size_list, local_size)
    size_list = [int(size.item()) for size in size_list]
    max_size = max(size_list)

    # receiving Tensor from all ranks
    # we pad the tensor because torch all_gather does not support
    # gathering tensors of different shapes
    tensor_list = []
    for _ in size_list:
        tensor_list.append(torch.empty((max_size,), dtype=torch.uint8, device="cuda"))
    if local_size != max_size:
        padding = torch.empty(size=(max_size - local_size,), dtype=torch.uint8, device="cuda")
        tensor = torch.cat((tensor, padding), dim=0)
    dist.all_gather(tensor_list, tensor)

    data_list = []
    for size, tensor in zip(size_list, tensor_list):
        buffer = tensor.cpu().numpy().tobytes()[:size]
        data_list.append(pickle.loads(buffer))

    return data_list


def reduce_dict(input_dict, average=True):
    """
    Args:
        input_dict (dict): all the values will be reduced
        average (bool): whether to do average or sum
    Reduce the values in the dictionary from all processes so that all processes
    have the averaged results. Returns a dict with the same fields as
    input_dict, after reduction.
    """
    world_size = get_world_size()
    if world_size < 2:
        return input_dict
    with torch.no_grad():
        names = []
        values = []
        # sort the keys so that they are consistent across processes
        for k in sorted(input_dict.keys()):
            names.append(k)
            values.append(input_dict[k])
        values = torch.stack(values, dim=0)
        dist.all_reduce(values)
        if average:
            values /= world_size
        reduced_dict = {k: v for k, v in zip(names, values)}
    return reduced_dict


class MetricLogger(object):
    def __init__(self, delimiter="\t"):
        self.meters = defaultdict(SmoothedValue)
        self.delimiter = delimiter

    def update(self, **kwargs):
        for k, v in kwargs.items():
            if isinstance(v, torch.Tensor):
                v = v.item()
            assert isinstance(v, (float, int))
            self.meters[k].update(v)

    def __getattr__(self, attr):
        if attr in self.meters:
            return self.meters[attr]
        if attr in self.__dict__:
            return self.__dict__[attr]
        raise AttributeError("'{}' object has no attribute '{}'".format(
            type(self).__name__, attr))

    def __str__(self):
        loss_str = []
        for name, meter in self.meters.items():
            loss_str.append(
                "{}: {}".format(name, str(meter))
            )
        return self.delimiter.join(loss_str)

    def synchronize_between_processes(self):
        for meter in self.meters.values():
            meter.synchronize_between_processes()

    def add_meter(self, name, meter):
        self.meters[name] = meter

    def log_every(self, iterable, print_freq, header=None):
        i = 0
        if not header:
            header = ''
        start_time = time.time()
        end = time.time()
        iter_time = SmoothedValue(fmt='{avg:.4f}')
        data_time = SmoothedValue(fmt='{avg:.4f}')
        space_fmt = ':' + str(len(str(len(iterable)))) + 'd'
        if torch.cuda.is_available():
            log_msg = self.delimiter.join([
                header,
                '[{0' + space_fmt + '}/{1}]',
                'eta: {eta}',
                '{meters}',
                'time: {time}',
                'data: {data}',
                'max mem: {memory:.0f}'
            ])
        else:
            log_msg = self.delimiter.join([
                header,
                '[{0' + space_fmt + '}/{1}]',
                'eta: {eta}',
                '{meters}',
                'time: {time}',
                'data: {data}'
            ])
        MB = 1024.0 * 1024.0
        for obj in iterable:
            data_time.update(time.time() - end)
            yield obj
            iter_time.update(time.time() - end)
            if i % print_freq == 0 or i == len(iterable) - 1:
                eta_seconds = iter_time.global_avg * (len(iterable) - i)
                eta_string = str(datetime.timedelta(seconds=int(eta_seconds)))
                if torch.cuda.is_available():
                    print(log_msg.format(
                        i, len(iterable), eta=eta_string,
                        meters=str(self),
                        time=str(iter_time), data=str(data_time),
                        memory=torch.cuda.max_memory_allocated() / MB))
                else:
                    print(log_msg.format(
                        i, len(iterable), eta=eta_string,
                        meters=str(self),
                        time=str(iter_time), data=str(data_time)))
            i += 1
            end = time.time()
        total_time = time.time() - start_time
        total_time_str = str(datetime.timedelta(seconds=int(total_time)))
        print('{} Total time: {} ({:.4f} s / it)'.format(
            header, total_time_str, total_time / len(iterable)))


def collate_fn(batch):
    return tuple(zip(*batch))


def warmup_lr_scheduler(optimizer, warmup_iters, warmup_factor):

    def f(x):
        if x >= warmup_iters:
            return 1
        alpha = float(x) / warmup_iters
        return warmup_factor * (1 - alpha) + alpha

    return torch.optim.lr_scheduler.LambdaLR(optimizer, f)


def mkdir(path):
    try:
        os.makedirs(path)
    except OSError as e:
        if e.errno != errno.EEXIST:
            raise


def setup_for_distributed(is_master):
    """
    This function disables printing when not in master process
    """
    import builtins as __builtin__
    builtin_print = __builtin__.print

    def print(*args, **kwargs):
        force = kwargs.pop('force', False)
        if is_master or force:
            builtin_print(*args, **kwargs)

    __builtin__.print = print


def is_dist_avail_and_initialized():
    if not dist.is_available():
        return False
    if not dist.is_initialized():
        return False
    return True


def get_world_size():
    if not is_dist_avail_and_initialized():
        return 1
    return dist.get_world_size()


def get_rank():
    if not is_dist_avail_and_initialized():
        return 0
    return dist.get_rank()


def is_main_process():
    return get_rank() == 0


def save_on_master(*args, **kwargs):
    if is_main_process():
        torch.save(*args, **kwargs)


def init_distributed_mode(args):
    if 'RANK' in os.environ and 'WORLD_SIZE' in os.environ:
        args.rank = int(os.environ["RANK"])
        args.world_size = int(os.environ['WORLD_SIZE'])
        args.gpu = int(os.environ['LOCAL_RANK'])
    elif 'SLURM_PROCID' in os.environ:
        args.rank = int(os.environ['SLURM_PROCID'])
        args.gpu = args.rank % torch.cuda.device_count()
    else:
        print('Not using distributed mode')
        args.distributed = False
        return

    args.distributed = True

    torch.cuda.set_device(args.gpu)
    args.dist_backend = 'nccl'
    print('| distributed init (rank {}): {}'.format(
        args.rank, args.dist_url), flush=True)
    torch.distributed.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
                                         world_size=args.world_size, rank=args.rank)
    torch.distributed.barrier()
    setup_for_distributed(args.rank == 0)