Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
训练自定义数据问题
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- Dominant language
- Python
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Description
你好，非常感谢你们的杰出工作。我按照文档训练自定义数据，按照VOC的格式转换了数据，训练完成后，有部分的非目标物体被误检，然后我加入了部分不含标注信息的样本，想要减少误检，训练流程正常通过，但是评估时报KeyError。
请问训练时是如何处理不带标注的样本的？或者是否有其他方法减少非目标物体的误检？谢谢
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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
Review the documentation's custom-data and VOC guidance, then trace the training and evaluation entry points involved in this report. Reproduce the run with and without unlabeled samples, inspect the KeyError, and document the supported handling and a verified way to reduce false positives.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100