mirror of https://github.com/open-mmlab/mmyolo.git
1.2 KiB
1.2 KiB
MMYOLO Model Assigner Visualization
Introduction
This project is developed for easily showing assigning results. The script allows users to analyze where and how many positive samples each gt is assigned in the image.
Now, the script supports YOLOv5 and RTMDet.
Usage
Command
python projects/assigner_visualization/assigner_visualization.py projects/assigner_visualization/configs/yolov5_s-v61_syncbn_fast_8xb16-300e_coco_assignervisualization.py
Note: YOLOv5 does not need to load the trained weights.
python projects/assigner_visualization/assigner_visualization.py projects/assigner_visualization/configs/rtmdet_s_syncbn_fast_8xb32-300e_coco_assignervisualization.py -c ${checkpont}
${checkpont} is the checkpont file path. Dynamic label assignment is used in RTMDet, model weights will affect the positive sample allocation results, so it is recommended to load the trained model weights.
If you want to know details about label assignment, you can check the documentation.