Function main

dataset_loaders/cambridge_scenes.py:257–287

visualizes the dataset

()

      return img, pose

def main():
  """
  visualizes the dataset
  """
  #from common.vis_utils import show_batch, show_stereo_batch
  from torchvision.utils import make_grid
  import torchvision.transforms as transforms
  seq = 'ShopFacade'
  mode = 1
  # num_workers = 1

  # transformer
  data_transform = transforms.Compose([
        transforms.ToTensor(),
        ])
  target_transform = transforms.Lambda(lambda x: torch.Tensor(x))
  kwargs = dict(ret_hist=True)
  dset = Cambridge2(seq, '../data/Cambridge/', True, data_transform, target_transform=target_transform, mode=mode, df=7.15, trainskip=2, **kwargs)
  print('Loaded Cambridge sequence {:s}, length = {:d}'.format(seq, len(dset)))

  data_loader = data.DataLoader(dset, batch_size=4, shuffle=False)

  batch_count = 0
  N = 2
  for batch in data_loader:
    print('Minibatch {:d}'.format(batch_count))
    pdb.set_trace()

    batch_count += 1
    if batch_count >= N:
      break

if __name__ == '__main__':
  main()