16 bits png support and compatibility with current transforms

We added support for decoding 16 bit pngs in https://github.com/pytorch/vision/pull/4657.

Pytorch doesn’t support uint16 dtype, so we have to return a int32 tenor instead. However as @nairbv pointed out, this can lead to unexpected behaviour for the convert_image_dtype(), because this function relies on the max value of a given dtype to carry the conversions.

While the actual max value of a 16 bits image is 2**16 - 1, convert_image_dtype() will assume that it’s (2**31 - 1) because the image is in a int32 tensor. This leads to e.g. a tensor full of zeros when converting to uint8.

Potential solutions are:

• native support for int16 in pytorch
• add a new input_range=None parameter to convert_image_dtype() (not a fan of that)

For now, I’ll just make this a private API (e.g. _decode_16bits_png() or something). It will still allow to continue the work on RAFT, which was the main reason I needed 16bits decoding in the first place.

[datumbox]

@NicolasHug I’ll try to have a look to get these examples. Another idea discussed on Github issues was also to store this information on the new Image classes that @pmeier is working on. This way we won’t have to pass an extra parameter and we can read this info directly from the input tensor meta-data.

[h-vetinari]

If I had to take a wild guess, I would bet that your CI pipeline is setup in such a way that 16 is part of the path to the images, even those that aren’t 16bits images. From your logs the image paths look like img_path = '$SRC_DIR/test/assets/fakedata/logos/gray_pytorch.png'. Does $SRC_DIR contain 16?

That was a great guess:

## Package Plan ##

  environment location: /home/conda/feedstock_root/build_artifacts/torchvision-split_1647851964444/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehol

If that’s the case please let us know and we’ll make that check more robust

That would be wonderful, thanks a lot! 🙃