shuuchen

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',
 9: 'ostrich, Struthio camelus',

shuuchen

import pickle
import numpy as np
import pdb

img_width, img_height = 300, 300
box_configs = [
    {'layer_width': 38, 'layer_height': 38, 'num_prior': 3, 'min_size':  30.0,
     'max_size': None, 'aspect_ratios': [1.0, 2.0, 1/2.0]},
    {'layer_width': 19, 'layer_height': 19, 'num_prior': 6, 'min_size':  60.0,
     'max_size': 114.0, 'aspect_ratios': [1.0, 1.0, 2.0, 1/2.0, 3.0, 1/3.0]},

shuuchen

C:\Users\to>python
Python 3.6.4 |Anaconda custom (64-bit)| (default, Jan 16 2018, 10:22:32) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> import sys
>>> sys.executable
'C:\\Users\\to\\Anaconda3\\python.exe'

shuuchen

class ImageFolderWithPaths(datasets.ImageFolder):
    """Custom dataset that includes image file paths. Extends
    torchvision.datasets.ImageFolder
    """

    # override the __getitem__ method. this is the method dataloader calls
    def __getitem__(self, index):
        # this is what ImageFolder normally returns 
        original_tuple = super(ImageFolderWithPaths, self).__getitem__(index)
        # the image file path

shuuchen

import torchvision.transforms.functional as F
import numpy as np
from PIL import Image
import os
from matplotlib import pyplot as plt

# input images
d = '../data/homes/test_input/'
img0 = Image.open(os.path.join(d, '352.jpg'))
img1 = Image.open(os.path.join(d, '95.jpg'))

shuuchen

from collections import defaultdict

class TrieNode:
    def __init__(self):
        self.isWord = False
        self.children = defaultdict(TrieNode)


class Trie:
    def __init__(self):

shuuchen

This post shows how to deal with the following error:
 
  (base) [dushu@ip-172-20-149-210 ~]$ nvidia-smi
  NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. 
  Make sure that the latest NVIDIA driver is installed and running.

Solution
  Just install the latest nvidia driver.

Process

shuuchen

class UT:
    def __init__(self, n):
        self.ps = list(range(n))
        self.rs = [0] * n

    def find(self, x):
        if self.ps[x] != x:
            self.ps[x] = self.find(self.ps[x])
        return self.ps[x]

shuuchen

from collections import defaultdict
from heapq import *

def dijkstra(edges, f, t):
    g = defaultdict(list)

    for l, r, c in edges:
        g[l].append((c, r))

    q, seen, mins = [(0, f, ())], set(), {f: 0}

shuuchen

class SiameseNetwork(nn.Module):
    def __init__(self):
        super(SiameseNetwork, self).__init__()
        
        self.cnn1 = nn.Sequential(
            nn.ReflectionPad2d(1),
            nn.Conv2d(1, 4, kernel_size=3),
            nn.ReLU(inplace=True),
            nn.BatchNorm2d(4),