Fix pil_to_tensor for 16-bit images - #9640
Conversation
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/vision/9640
Note: Links to docs will display an error until the docs builds have been completed. This comment was automatically generated by Dr. CI and updates every 15 minutes. |
|
Hi @Marchematics! Thank you for your pull request and welcome to our community. Action RequiredIn order to merge any pull request (code, docs, etc.), we require contributors to sign our Contributor License Agreement, and we don't seem to have one on file for you. ProcessIn order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA. Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with If you have received this in error or have any questions, please contact us at cla@meta.com. Thanks! |
There was a problem hiding this comment.
Pull request overview
This PR updates torchvision.transforms.functional.pil_to_tensor to correctly convert 16-bit PIL images into Torch tensors (instead of failing or producing incorrect dtypes), and adds a regression test to validate round-tripping of int16 tensors through ToPILImage + PILToTensor.
Changes:
- Add explicit PIL mode → NumPy dtype mapping in
pil_to_tensorto support 16-bit (I;16) images. - Add a unit test that exercises
int16tensor → PIL → tensor conversion.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
torchvision/transforms/functional.py |
Adds dtype selection logic in pil_to_tensor to handle 16-bit PIL modes. |
test/test_transforms.py |
Adds a regression test ensuring int16 round-trips through PIL conversion. |
💡 Add a code-review agent skill or configure MCP servers for context-aware, tailored reviews. Learn more in the docs.
| mode_to_nptype = { | ||
| "I": np.int32, | ||
| "I;16" if sys.byteorder == "little" else "I;16B": np.int16, | ||
| "F": np.float32, | ||
| } | ||
| img = torch.as_tensor(np.array(pic, mode_to_nptype.get(pic.mode, np.uint8), copy=True)) |
|
Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Meta Open Source project. Thanks! |
|
Added explicit I;16 and I;16B mappings with regression coverage. |
159da63 to
b7db05b
Compare
Fix pil_to_tensor for 16-bit images.