pytorch 批次遍历数据集打印数据的例子

Python  /  管理员 发布于 5年前   201

我就废话不多说了，直接上代码吧！

from os import listdirimport osfrom time import time import torch.utils.data as dataimport torchvision.transforms as transformsfrom torch.utils.data import DataLoader def printProgressBar(iteration, total, prefix='', suffix='', decimals=1, length=100,           fill='=', empty=' ', tip='>', begin='[', end=']', done="[DONE]", clear=True):  percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))  filledLength = int(length * iteration // total)  bar = fill * filledLength  if iteration != total:    bar = bar + tip  bar = bar + empty * (length - filledLength - len(tip))  display = '\r{prefix}{begin}{bar}{end} {percent}%{suffix}' \    .format(prefix=prefix, begin=begin, bar=bar, end=end, percent=percent, suffix=suffix)  print(display, end=''), # comma after print() required for python 2  if iteration == total: # print with newline on complete    if clear: # display given complete message with spaces to 'erase' previous progress bar      finish = '\r{prefix}{done}'.format(prefix=prefix, done=done)      if hasattr(str, 'decode'): # handle python 2 non-unicode strings for proper length measure        finish = finish.decode('utf-8')        display = display.decode('utf-8')      clear = ' ' * max(len(display) - len(finish), 0)      print(finish + clear)    else:      print('')  class DatasetFromFolder(data.Dataset):  def __init__(self, image_dir):    super(DatasetFromFolder, self).__init__()    self.photo_path = os.path.join(image_dir, "a")    self.sketch_path = os.path.join(image_dir, "b")    self.image_filenames = [x for x in listdir(self.photo_path) if is_image_file(x)]     transform_list = [transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]     self.transform = transforms.Compose(transform_list)   def __getitem__(self, index):    # Load Image    input = load_img(os.path.join(self.photo_path, self.image_filenames[index]))    input = self.transform(input)    target = load_img(os.path.join(self.sketch_path, self.image_filenames[index]))    target = self.transform(target)     return input, target   def __len__(self):    return len(self.image_filenames) if __name__ == '__main__':  dataset = DatasetFromFolder("./dataset/facades/train")  dataloader = DataLoader(dataset=dataset, num_workers=8, batch_size=1, shuffle=True)  total = len(dataloader)  for epoch in range(20):    t0 = time()    for i, batch in enumerate(dataloader):      real_a, real_b = batch[0], batch[1]      printProgressBar(i + 1, total + 1,   length=20,   prefix='Epoch %s ' % str(1),   suffix=', d_loss: %d' % 1)    printProgressBar(total, total, done='Epoch [%s] ' % str(epoch) +   ', time: %.2f s' % (time() - t0) )

以上这篇pytorch 批次遍历数据集打印数据的例子就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。