Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
check a speed of model
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- Dominant language
- Python
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Description
Hi, I'm currently using a model yolox-s for mobile.
I want to compare the speed between original yolox-s model and my own trained based on yolox-s.
So, I compared with them with onnxruntime demo and checking time in colab like below.
%load_ext autotime
python3 onnx_inference.py -m <ONNX_MODEL_PATH> -i <IMAGE_PATH> -o <OUTPUT_DIR> -s 0.3 --input_shape 640,640
Is it correct way to compare execution time for model?
Is there any suggestion to benchmark a model? like checking GFLOPs, fps or latency.
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Research direction
Start with the referenced onnx_inference.py command and the Colab timing setup, then review the repository's existing model and deployment documentation for benchmarking guidance. A useful outcome would be a documented, reproducible way to compare the original and trained YOLOX-s models using latency, FPS, or GFLOPs.
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Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100