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# -*- coding: utf-8 -*-
import os
import requests

conf = 'CVPR2016' # CVPR2015/CVPR2014/CVPR2013/ICCV2013
#header = 'http://www.cv-foundation.org/openaccess/'
header = 'http://openaccess.thecvf.com/'

def name_check(name):
    name = name.replace('?','')

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# coding: utf-8

import os
import os.path
import fnmatch
import subprocess
import argparse

# Parse the arguments
parser = argparse.ArgumentParser(description='Tile the first num-pages horizontally into a JPEG image.')

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from visdom import Visdom
import argparse
import numpy as np


DEFAULT_PORT = 8097
DEFAULT_HOSTNAME = "http://localhost"
parser = argparse.ArgumentParser(description='Demo arguments')
parser.add_argument('-port', metavar='port', type=int, default=DEFAULT_PORT, help='port the visdom server is running on.')
parser.add_argument('-server', metavar='server', type=str, default=DEFAULT_HOSTNAME, help='Server address of the target to run the demo on.')

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# This code is for self study.
# Remider of the difference between copy.copy and copy.deepcopy

# immutable objects
print('immutable object')
a = 'abc'
b = a

print("a:{}, id(a):{}".format(a, id(a)))
print("b:{}, id(b):{}".format(b, id(b)))

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from tqdm import tqdm
import time
from collections import OrderedDict
from random import random

with tqdm(range(10000), ncols=10) as pbar:
	for i in pbar:
		pbar.set_postfix(OrderedDict(
			output='{:06d}'.format(i),
			loss='{:.4f}'.format(random())

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import os
import tqdm
import argparse

import torch
import torch.nn as nn
import torchvision

from skimage.io import imread, imsave

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import random
import numpy as np

import copy

import torch
import torchvision
from torchvision import transforms

from PIL import Image

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import os
import sys

import torch
import torch.nn.functional as F

import pymesh

class VisCameras():
	init_front_vec = torch.tensor([1.0, 0.0, 0.0]).view(1,-1).float()

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import os
import sys

import torch
import torch.nn.functional as F

import pymesh

class VisCameras():
	init_front_vec = torch.tensor([1.0, 0.0, 0.0]).view(1,-1).float()

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import os
import argparse
import glob

import torch
import torch.nn as nn
import numpy as np
from skimage.io import imread, imsave
import tqdm
import imageio