Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
Does training image dimension need to be square shape for good performance
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Description
I am training yolox_tiny on say 320x192 image dimension and I see a 10% difference between validation score and test score. The difference is not that high when I train with a square shaped image such as 416x416 on the same dataset.
Is this expected? Have you done any testing with image input shape that are not square shape?
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Research direction
Start by reproducing the YOLOX-Tiny training comparison with 320x192 and 416x416 inputs on the same dataset. Trace how non-square image dimensions are handled during training, validation, and testing, then determine whether the score difference is expected and document the finding or identify a reproducible defect.
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Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100