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Lucas David lucasdavid

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lucasdavid / test_voc_colormap.py
Last active December 16, 2022 18:46
Test which option translates segmentation masks pixels faster
import argparse
import os
import time
import numpy as np
import tensorflow as tf
parser = argparse.ArgumentParser()
parser.add_argument('--opt', default='a', choices=['a', 'b'])
parser.add_argument('--batch_size', type=int, default=32)
@lucasdavid
lucasdavid / brazilNamesGenderRatio4.tsv
Last active February 6, 2024 19:48
firstName total female male totalFound prFemale
0SEAS 1 0 1 1 0.0000000000
0SMAR 1 0 1 1 0.0000000000
A 1 0 1 1 0.0000000000
AARAO 2 0 2 2 0.0000000000
DIARONE 6 0 6 6 0.0000000000
DIARONI 4 0 4 4 0.0000000000
DIASIS 1 0 1 1 0.0000000000
DIASLINS 1 0 1 1 0.0000000000
@lucasdavid
lucasdavid / cifar100-sequence-training-example.py
Created June 10, 2018 23:04
Training a classifier on cifar100, using full TB functionality
import tensorflow as tf
from keras.callbacks import TensorBoard
from keras.datasets import cifar100
from keras.layers import Dense, Conv2D, MaxPooling2D, GlobalAveragePooling2D, BatchNormalization, Activation, Dropout
from keras.layers import Input
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
from sacred import Experiment
ex = Experiment('tb-efficiency')
@lucasdavid
lucasdavid / cifar100-sequence-training-example.py
Created June 10, 2018 23:04
Training a classifier on cifar100, using full TB functionality
import tensorflow as tf
from keras.callbacks import TensorBoard
from keras.datasets import cifar100
from keras.layers import Dense, Conv2D, MaxPooling2D, GlobalAveragePooling2D, BatchNormalization, Activation, Dropout
from keras.layers import Input
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
from sacred import Experiment
ex = Experiment('tb-efficiency')
@lucasdavid
lucasdavid / cifar100-training-example.py
Created May 15, 2018 00:41
import tensorflow as tf
from keras.callbacks import TensorBoard
from keras.datasets import cifar100
from keras.layers import Dense, Conv2D, MaxPooling2D, GlobalAveragePooling2D, BatchNormalization, Activation, Dropout
from keras.layers import Input
from keras.models import Model
from sacred import Experiment
ex = Experiment('tb-efficiency')
@lucasdavid
lucasdavid / model_retraining.py
Created December 11, 2017 18:08
Demonstrates correct behavior of TensorBoard callback on model re-training.
import numpy as np
from keras import Input
from keras.layers import Dense
from keras.models import Model
from keras import callbacks
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
def build_model(shape, name=None):
x = Input(shape)
@lucasdavid
lucasdavid / show_triplet_model_throws_error.py
Created February 24, 2017 20:56
Show that we cannot call model.predict inside the generator that feeds model.fit.
import numpy as np
from keras import backend as K
from keras.datasets import cifar10
from keras.engine import Input, Model
from keras.models import Sequential
from keras.layers import Dense, Lambda
def build_model(x_shape):
b_net = Sequential([