AttributeError: 'NoneType' object has no attribute 'astype'

你。 提交于 2021-01-24 07:14:59

问题


I encountered the following problem when I reproduce the ESRGAN related program. libpng error: Read Error

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'

I tried to find the code for the line where the error occurred.

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}

I feel that the picture I read in has gone wrong. One of them reads in and is None. I don't know how to deal with this problem. I am running this program with the NVIDIA Tesla P100GPU.

19-08-30 06:12:28.193 - INFO: 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: 7.0139e+00 D_fake: -1.3881e+01 19-08-30 06:14:34.038 - INFO: 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: 7.1848e+00 D_fake: -8.6396e+00 19-08-30 06:16:38.986 - INFO: 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: 1.6663e+01 D_fake: 9.5084e+00 19-08-30 06:18:42.645 - INFO: 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: 1.0516e+00 D_fake: -8.9531e+00 libpng error: Read Error Traceback (most recent call last):

………………


回答1:


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.



来源:https://stackoverflow.com/questions/57273464/attributeerror-nonetype-object-has-no-attribute-astype

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