Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
Intermediate feature visualization
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- Dominant language
- Python
- Stars
- 10.6k
- Forks
- 2.5k
- PR merge metrics
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Description
How can I visualize the features generated by the intermediate layers of the YOLOX model?
Contributor guide
No contributing guide indexed for this repository
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
The issue names no file, test, or entry point. Start by locating the YOLOX model's intermediate layers and any existing visualization guidance, then determine whether the request requires documentation or a new feature. Done means a reproducible way to visualize features generated by intermediate layers.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100