docs: Details for ambigious channel dimension assignment #37600
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stevhliu
reviewed
Apr 18, 2025
src/transformers/image_utils.py
Outdated
| @@ -368,7 +368,7 @@ def infer_channel_dimension_format( | |||
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| if image.shape[first_dim] in num_channels and image.shape[last_dim] in num_channels: | |||
| logger.warning( | |||
| f"The channel dimension is ambiguous. Got image shape {image.shape}. Assuming channels are the first dimension." | |||
| f"The channel dimension is ambiguous. Got image shape {image.shape}. Assuming channels are the first dimension. Use the `input_data_format` parameter to assign the channel dimension, more details in `https://huggingface.co/docs/transformers/main/internal/image_processing_utils#transformers.image_transforms.rescale.input_data_format`." | |||
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cc @qubvel, would you mind taking a quick look and verifying this please? 🤗
Suggested change
| f"The channel dimension is ambiguous. Got image shape {image.shape}. Assuming channels are the first dimension. Use the `input_data_format` parameter to assign the channel dimension, more details in `https://huggingface.co/docs/transformers/main/internal/image_processing_utils#transformers.image_transforms.rescale.input_data_format`." | |
| f"The channel dimension is ambiguous. Got image shape {image.shape}. Assuming channels are the first dimension. Use the [input_data_format](https://huggingface.co/docs/transformers/main/internal/image_processing_utils#transformers.image_transforms.rescale.input_data_format) parameter to assign the channel dimension." |
Co-authored-by: Steven Liu <[email protected]>
yaner-here
changed the title
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Hi, any progress? |
qubvel
approved these changes
Apr 29, 2025
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
zucchini-nlp
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May 14, 2025
…#37600) * docs: Details for ambigious channel dimension inference * Update src/transformers/image_utils.py Co-authored-by: Steven Liu <[email protected]> --------- Co-authored-by: Steven Liu <[email protected]>
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What does this PR do?
Refined docs on how to assign channel dimension of inputs.
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