Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
Rectangle shape supported
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- Dominant language
- Python
- Stars
- 10.6k
- Forks
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Description
yolox 是否支持矩形框预测？我尝试export onnx 调整test size 但没有成功。使用了自己的数据，1920*1080的图片，实际测试中yolox nano/tiny 在preprocess和infer阶段耗时相对yolo5s 模型会略高，640 input size pre+infer+nms fps有15%-20%的降低， 测试环境4C8G 1GPU(T4)
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by tracing YOLOX's ONNX export path and the test-size and preprocess configuration mentioned in the issue. Compare how rectangular 1920×1080 inputs flow through preprocessing, inference, and NMS, then define and validate what rectangular-input support should mean for export and runtime behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100