我在复现ESRGAN相关程序时遇到了如下问题。 libpng 错误:读取错误

Traceback (most recent call last):
  File "/sda/ZTL/B/codes/train.py", line 173, in <module>
    main()
  File "/sda/ZTL/B/codes/train.py", line 97, in main
    for _, train_data in enumerate(train_loader):
  File "/root/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 637, in __next__
    return self._process_next_batch(batch)
  File "/root/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 658, in _process_next_batch
    raise batch.exc_type(batch.exc_msg)
AttributeError: Traceback (most recent call last):
  File "/root/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
    samples = collate_fn([dataset[i] for i in batch_indices])
  File "/root/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in <listcomp>
    samples = collate_fn([dataset[i] for i in batch_indices])
  File "/sda/ZTL/B/data/LRHR_dataset.py", line 51, in __getitem__
    img_HR = util.read_img(self.HR_env, HR_path)
  File "/sda/ZTL/B/data/util.py", line 79, in read_img
    img = img.astype(np.float32) / 255.
AttributeError: 'NoneType' object has no attribute 'astype'

我试图找到发生错误的行的代码。

File "/sda/ZTL/B/data/util.py", line 79, in read_img
def read_img(env, path):
    # read image by cv2 or from lmdb
    # return: Numpy float32, HWC, BGR, [0,1]
    if env is None:  # img
        img = cv2.imread(path, cv2.IMREAD_UNCHANGED)
    else:
        img = _read_lmdb_img(env, path)
    img = img.astype(np.float32) / 255.
    if img.ndim == 2:
        img = np.expand_dims(img, axis=2)
    # some images have 4 channels
    if img.shape[2] > 3:
        img = img[:, :, :3]
    return img

File "/sda/ZTL/B/data/LRHR_dataset.py", line 51, in __getitem__
 def __getitem__(self, index):
        HR_path, LR_path = None, None
        scale = self.opt['scale']
        HR_size = self.opt['HR_size']

        # get HR image
        HR_path = self.paths_HR[index]
        img_HR = util.read_img(self.HR_env, HR_path)
        # modcrop in the validation / test phase
        if self.opt['phase'] != 'train':
            img_HR = util.modcrop(img_HR, scale)
        # change color space if necessary
        if self.opt['color']:
            img_HR = util.channel_convert(img_HR.shape[2], self.opt['color'], [img_HR])[0]

        # get LR image
        if self.paths_LR:
            LR_path = self.paths_LR[index]
            img_LR = util.read_img(self.LR_env, LR_path)
        else:  # down-sampling on-the-fly
            # randomly scale during training
            if self.opt['phase'] == 'train':
                random_scale = random.choice(self.random_scale_list)
                H_s, W_s, _ = img_HR.shape

                def _mod(n, random_scale, scale, thres):
                    rlt = int(n * random_scale)
                    rlt = (rlt // scale) * scale
                    return thres if rlt < thres else rlt

                H_s = _mod(H_s, random_scale, scale, HR_size)
                W_s = _mod(W_s, random_scale, scale, HR_size)
                img_HR = cv2.resize(np.copy(img_HR), (W_s, H_s), interpolation=cv2.INTER_LINEAR)
                # force to 3 channels
                if img_HR.ndim == 2:
                    img_HR = cv2.cvtColor(img_HR, cv2.COLOR_GRAY2BGR)

            H, W, _ = img_HR.shape
            # using matlab imresize
            img_LR = util.imresize_np(img_HR, 1 / scale, True)
            if img_LR.ndim == 2:
                img_LR = np.expand_dims(img_LR, axis=2)

        if self.opt['phase'] == 'train':
            # if the image size is too small
            H, W, _ = img_HR.shape
            if H < HR_size or W < HR_size:
                img_HR = cv2.resize(
                    np.copy(img_HR), (HR_size, HR_size), interpolation=cv2.INTER_LINEAR)
                # using matlab imresize
                img_LR = util.imresize_np(img_HR, 1 / scale, True)
                if img_LR.ndim == 2:
                    img_LR = np.expand_dims(img_LR, axis=2)
                    print(img_LR)

            H, W, C = img_LR.shape
            LR_size = HR_size // scale

            # randomly crop
            rnd_h = random.randint(0, max(0, H - LR_size))
            rnd_w = random.randint(0, max(0, W - LR_size))
            img_LR = img_LR[rnd_h:rnd_h + LR_size, rnd_w:rnd_w + LR_size, :]
            rnd_h_HR, rnd_w_HR = int(rnd_h * scale), int(rnd_w * scale)
            img_HR = img_HR[rnd_h_HR:rnd_h_HR + HR_size, rnd_w_HR:rnd_w_HR + HR_size, :]

            # augmentation - flip, rotate
            img_LR, img_HR = util.augment([img_LR, img_HR], self.opt['use_flip'], \
                self.opt['use_rot'])

        # change color space if necessary
        if self.opt['color']:
            img_LR = util.channel_convert(C, self.opt['color'], [img_LR])[0] # TODO during val no definetion

        # BGR to RGB, HWC to CHW, numpy to tensor
        if img_HR.shape[2] == 3:
            img_HR = img_HR[:, :, [2, 1, 0]]
            img_LR = img_LR[:, :, [2, 1, 0]]
        img_HR = torch.from_numpy(np.ascontiguousarray(np.transpose(img_HR, (2, 0, 1)))).float()
        img_LR = torch.from_numpy(np.ascontiguousarray(np.transpose(img_LR, (2, 0, 1)))).float()

        if LR_path is None:
            LR_path = HR_path
        return {'LR': img_LR, 'HR': img_HR, 'LR_path': LR_path, 'HR_path': HR_path}

感觉读进去的图有问题。其中一个读入并且是无。我不知道如何处理这个问题。我正在使用 NVIDIA Tesla P100GPU 运行这个程序。

19-08-30 06:12:28.193 - 信息:l_g_pix:3.9939e-03 l_g_fea:2.3352e+00 l_g_gan:1.0448e-01 l_d_real:1.5721e-06 l_d_fake:1.6599e-05 D_real:e 7.0139 +00 D_fake:-1.3881e+01 19-08-30 06:14:34.038 - 信息:l_g_pix:2.9632e-03 l_g_fea:1.7633e+00 l_g_gan:7.9122e-02 l_d_real:5.6028e-06 l_d_fake:4.7490e-05 D_real:7.1848fakee :-8.6396e+00 19-08-30 06:16:38.986 - 信息:l_g_pix:3.6181e-03 l_g_fea:2.2983e+00 l_g_gan:3.5791e-02 l_d_real:3.3302e-03 l_d_fake:2.6311e-03 D_real:+0.61663fakee : 9.5084e+00 19-08-30 06:18:42.645 - 信息:l_g_pix:3.9908e-03 l_g_fea:2.1037e+00 l_g_gan:5.0026e-02 l_d_real:2.2486e-04 l_d_fake:7.5957e-04 D_real:+00 D_fakefake : -8.9531e+00 libpng 错误:读取错误 追溯(最近一次通话最后一次):

………………

最佳答案

1) check the image path is correct.

2) make sure that image is read as numpy ndarray e.g(using matplotlib, cv2), using PIL it reads image in another format so it becomes impossible to apply numpy array operations.

关于python-3.x - 属性错误 : 'NoneType' object has no attribute 'astype' ，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/57273464/