AttributeError: 'MpoImageFile' object has no attribute 'shape' - python-3.x

Question

images, labels = next(iter(self.loader))
grid = torchvision.utils.make_grid(images)
images, labels = next(iter(self.loader))
triggers the error.
I have a custom dataset class where I load each image (RGB) from an url :
image = Image.open(urllib.request.urlopen(URL))
and I apply some albumentations transforms.
The code works when I read an image for which I have a path using cv2.
However, it doesn't work when I read an image from the url.
Note that I verified that the urls aren't broken.
Here's the traceback:
/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in __next__(self)
344 def __next__(self):
345 index = self._next_index() # may raise StopIteration
--> 346 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
347 if self._pin_memory:
348 data = _utils.pin_memory.pin_memory(data)
/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py in <listcomp>(.0)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
/content/transform_dataset.py in __getitem__(self, idx)
49 labels = torch.from_numpy(item[2:].values.astype("float32"))
50 #print("self.root,item,self.image_transform,self.transform,self.size", self.root,item,self.image_transform,self.transform,self.size)
---> 51 image = load_image(self.root,item.ID,item.URL,self.image_transform)
52 return image, labels
53
/content/transform_dataset.py in load_image(root, ID, URL, image_transform)
81 print(image.shape)
82 image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
---> 83 image = image_transform(image=image)["image"]
84 return image
/usr/local/lib/python3.6/dist-packages/albumentations/core/composition.py in __call__(self, **data)
169 convert_keypoints_to_albumentations, data)
170
--> 171 data = t(**data)
172
173 if dual_start_end is not None and idx == dual_start_end[1]:
/usr/local/lib/python3.6/dist-packages/albumentations/core/transforms_interface.py in __call__(self, **kwargs)
26 if (random.random() < self.p) or self.always_apply:
27 params = self.get_params()
---> 28 params = self.update_params(params, **kwargs)
29 if self.targets_as_params:
30 targets_as_params = {k: kwargs[k] for k in self.targets_as_params}
/usr/local/lib/python3.6/dist-packages/albumentations/core/transforms_interface.py in update_params(self, params, **kwargs)
66 if hasattr(self, 'interpolation'):
67 params['interpolation'] = self.interpolation
---> 68 params.update({'cols': kwargs['image'].shape[1], 'rows': kwargs['image'].shape[0]})
69 return params
70
AttributeError: 'MpoImageFile' object has no attribute 'shape'

Answer 1

In order to work with albumentations, you must pass a numpy array to the transforms not a PIL image. So:
image = Image.open(urllib.request.urlopen(URL))
image = np.array(image)