fix load gif

[huarzone]

Training with GIF images

[gemini-code-assist]

Summary of Changes

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This pull request addresses an issue related to loading GIF images, particularly in the context of training with GIF datasets. It refines the data loading pipeline by adjusting how GIF frames are processed, ensuring that image manipulation operations like cropping and resizing are applied at the correct stage during GIF loading. This change aims to improve the robustness and correctness of GIF image handling for training purposes.

Highlights

• GIF Loading Logic Refinement: The LoadGIF operator in unified_dataset.py has been updated to accept ImageCropAndResize as a frame_processor argument. This change integrates image cropping and resizing directly into the GIF loading process, ensuring individual frames are processed correctly and efficiently.

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[gemini-code-assist]

Code Review

This pull request correctly fixes a bug in the GIF loading pipeline. Previously, the ImageCropAndResize operator was incorrectly applied to the entire list of frames from a GIF, which would cause a runtime error. The new implementation correctly passes ImageCropAndResize as a frame_processor to LoadGIF, ensuring each frame is processed individually. This aligns the GIF processing with the existing video processing logic and is a good improvement.

While this change is correct, I identified a performance issue in the LoadGIF class itself. It currently reads the entire GIF file into memory twice for each file processed—once in get_num_frames and again in the __call__ method. This is inefficient and could lead to high memory consumption and slow data loading, especially with large GIF files. I recommend refactoring the LoadGIF class in a follow-up pull request to read the file only once. This would significantly improve performance.