def test_prostate_dataloader(): root_dir = '../dataset/PROSTATE' train_dataset = MedicalImageDataset(root_dir, 'train', transform=segment_transform( (128, 128)), augment=augment) val_dataset = MedicalImageDataset(root_dir, 'val', transform=segment_transform((128, 128)), augment=None) train_loader = DataLoader(train_dataset, batch_size=1, shuffle=True) val_loader = DataLoader(val_dataset, batch_size=1, shuffle=False) # for i, (Img, GT, wgt, _) in enumerate(train_loader): # ToPILImage()(Img[0]).show() # if i == 5: # train_loader.dataset.set_mode('eval') # ToPILImage()(Img[0]).show() # if i == 10: # break # # for i, (img, gt, wgt, _) in enumerate(val_loader): # ToPILImage()(img[0]).show() # if i == 5: # val_loader.dataset.set_mode('eval') # ToPILImage()(img[0]).show() # if i == 10: # break assert train_dataset.__len__() == train_dataset.imgs.__len__()
def test_dataloader(): root_dir = '../dataset/ACDC-2D-All' train_dataset = MedicalImageDataset(root_dir, 'train', transform=segment_transform( (500, 500)), augment=augment) val_dataset = MedicalImageDataset(root_dir, 'val', transform=segment_transform((500, 500)), augment=None) train_loader = DataLoader(train_dataset, batch_size=1, shuffle=True) val_loader = DataLoader(val_dataset, batch_size=1, shuffle=False) for i, (Img, GT, wgt, _) in enumerate(train_loader): if GT.sum() <= 0 or wgt.sum() <= 0: continue show_img_mask_weakmask(Img.numpy(), GT.numpy(), wgt.numpy()) # # ToPILImage()(Img[0]).show() # if i == 5: # train_loader.dataset.set_mode('eval') # ToPILImage()(Img[0]).show() # if i == 10: # break # for i, (img, gt, wgt, _) in enumerate(val_loader): # ToPILImage()(img[0]).show() # if i == 5: # val_loader.dataset.set_mode('eval') # ToPILImage()(img[0]).show() # if i == 10: # break assert train_dataset.__len__() == train_dataset.imgs.__len__()