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include.py
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include.py
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import os
from datetime import datetime
PROJECT_PATH = os.path.dirname(os.path.realpath(__file__))
IDENTIFIER = datetime.now().strftime('%Y-%m-%d_%H-%M-%S')
import math
import numpy as np
import random
import PIL
import cv2
import torch
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
from torch.utils.data.sampler import *
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.nn.parallel.data_parallel import data_parallel
# std libs
import collections
import copy
import numbers
import inspect
import shutil
from timeit import default_timer as timer
import itertools
from collections import OrderedDict
import pandas as pd
import pickle
import glob
import sys
from distutils.dir_util import copy_tree
import time
from skimage.transform import resize as skimage_resize
# constant #
PI = np.pi
INF = np.inf
EPS = 1e-12
import os
from datetime import datetime
#numerical libs
import math
import numpy as np
import random
import PIL
import cv2
import torch
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
from torch.utils.data.sampler import *
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.nn.parallel.data_parallel import data_parallel
import collections
import copy
import numbers
import inspect
import shutil
from timeit import default_timer as timer
import itertools
from collections import OrderedDict
import csv
import pandas as pd
import pickle
import glob
import sys
from distutils.dir_util import copy_tree
import time
PI = np.pi
INF = np.inf
EPS = 1e-12
#---------------------------------------------------------------------------------
class Struct(object):
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
#---------------------------------------------------------------------------------
def remove_comments(lines, token='#'):
""" Generator. Strips comments and whitespace from input lines.
"""
l = []
for line in lines:
s = line.split(token, 1)[0].strip()
if s != '':
l.append(s)
return l
def remove(file):
if os.path.exists(file): os.remove(file)
def empty(dir):
if os.path.isdir(dir):
shutil.rmtree(dir, ignore_errors=True)
else:
os.makedirs(dir)
# http://stackoverflow.com/questions/34950201/pycharm-print-end-r-statement-not-working
class Logger(object):
def __init__(self):
self.terminal = sys.stdout #stdout
self.file = None
def open(self, file, mode=None):
if mode is None: mode ='w'
self.file = open(file, mode)
def write(self, message, is_terminal=1, is_file=1 ):
if '\r' in message: is_file=0
if is_terminal == 1:
self.terminal.write(message)
self.terminal.flush()
#time.sleep(1)
if is_file == 1:
self.file.write(message)
self.file.flush()
def flush(self):
# this flush method is needed for python 3 compatibility.
# this handles the flush command by doing nothing.
# you might want to specify some extra behavior here.
pass
# io ------------------------------------
def write_list_to_file(strings, list_file):
with open(list_file, 'w') as f:
for s in strings:
f.write('%s\n'%str(s))
pass
def read_list_from_file(list_file, comment='#', func=None):
with open(list_file) as f:
lines = f.readlines()
strings=[]
for line in lines:
s = line.split(comment, 1)[0].strip()
if s != '':
strings.append(s)
if func is not None:
strings=[func(s) for s in strings]
return strings
def load_pickle_file(pickle_file):
with open(pickle_file,'rb') as f:
x = pickle.load(f)
return x
def save_pickle_file(pickle_file, x):
with open(pickle_file, 'wb') as f:
pickle.dump(x, f, pickle.HIGHEST_PROTOCOL)
def backup_project_as_zip(project_dir, zip_file):
assert(os.path.isdir(project_dir))
assert(os.path.isdir(os.path.dirname(zip_file)))
shutil.make_archive(zip_file.replace('.zip',''), 'zip', project_dir)
pass
# etc ------------------------------------
def time_to_str(t, mode='min'):
if mode=='min':
t = int(t)/60
hr = t//60
min = t%60
return '%2d hr %02d min'%(hr,min)
elif mode=='sec':
t = int(t)
min = t//60
sec = t%60
return '%2d min %02d sec'%(min,sec)
else:
raise NotImplementedError
def np_float32_to_uint8(x, scale=255):
return (x*scale).astype(np.uint8)
def np_uint8_to_float32(x, scale=255):
return (x/scale).astype(np.float32)