microsoft / microsoft/onnxruntime-inference-examples
Reproducing the yolov8 model used in the Android object detection example.
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- C++
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Description
How exactly can the yolov8 binary model be reproduced? Running the pre and postprocessing script referenced from the readme yields a different model with only an image_out head whereas the model file in the sources has two more outputs (scaled_box_out_next and scaled_box_out_debug)
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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 with the README's referenced preprocessing and postprocessing script and compare its generated model with the model file in the Android object detection example. Determine why the generated graph exposes only image_out while the source model also has scaled_box_out_next and scaled_box_out_debug, then document the reproduction steps or discrepancy.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- android
- Domain
- computer-vision, machine-learning, mobile-dev
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100