Error fetching images will fail the infer method

[eitantorf]

I am trying to run transform_jsonl (to download images and prepare m3 json file) and right after running the infer method - the issue occurs when transform_jsonl does not find some images but still writes the path to the m3 json file, causing the infer to fail over:
FileNotFoundError: [Errno 2] No such file or directory

[computermacgyver]

Thank you @eitantorf for letting us know.

We're supposed to catch this and replace with the "default image" if the image is unavailable:

m3inference/m3inference/m3twitter.py

Lines 97 to 98 in b208bae

	if not os.path.exists(img_file_resize):
	img_file_resize = TW_DEFAULT_PROFILE_IMG

I'll have to look into it further. Would you be able to share an example of input and errant output? I'm curious if it is supposed to be a path to the default image but that the default image is unavailable or something else.

[eitantorf]

Ah I see you fixed it, great.
My code is the previous one I now see, maybe the pip install version does not include this fix?

[computermacgyver]

I'll check what on pip. Thanks, @eitantorf

[zijwang]

Thanks, @eitantorf and @computermacgyver! I have pushed the latest version to pypi. @eitantorf , could you try updating the package and see whether the issue persists?

[davidjurgens]

It might be worth extending this behavior to all image-related errors during inference. Here's one I just ran into where the file type can't be inferred, which causes the whole infer call to error out:

UnidentifiedImageError: Caught UnidentifiedImageError in DataLoader worker process 3.
Original Traceback (most recent call last):
  File "/opt/anaconda/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 202, in _worker_loop
    data = fetcher.fetch(index)
  File "/opt/anaconda/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/opt/anaconda/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/opt/anaconda/lib/python3.8/site-packages/m3inference/dataset.py", line 37, in __getitem__
    return self._preprocess_data(data)
  File "/opt/anaconda/lib/python3.8/site-packages/m3inference/dataset.py", line 43, in _preprocess_data
    fig = self._image_loader(img_path)
  File "/opt/anaconda/lib/python3.8/site-packages/m3inference/dataset.py", line 91, in _image_loader
    image = Image.open(image_name)
  File "/opt/anaconda/lib/python3.8/site-packages/PIL/Image.py", line 2958, in open
    raise UnidentifiedImageError(
PIL.UnidentifiedImageError: cannot identify image file 'someimage.jpg'

It's probably worth not failing in those cases and just printing a warning. That, or adding some kind of pandas-like flag errors='ignore' as the default and let the users decide if the infer should stop on error.