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Bug fix mAP0.5-0.95 #6787
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Bug fix mAP0.5-0.95 #6787
Commits on Feb 26, 2022
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Two changes provided 1. Added limit on the maximum number of detections for each image likewise pycocotools 2. Rework process_batch function Changes ultralytics#2 solved issue ultralytics#4251 I also independently encountered the problem described in issue ultralytics#4251 that the values for the same thresholds do not match when changing the limits in the torch.linspace function. These changes solve this problem. Currently during validation yolov5x.pt model the following results were obtained: from yolov5 validation Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 157/157 [01:07<00:00, 2.33it/s] all 5000 36335 0.743 0.626 0.682 0.506 from pycocotools Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.505 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.685 These results are very close, although not completely pass the competition issue ultralytics#2258. I think it's problem with false positive bboxes matched ignored criteria, but this is not actual for custom datasets and does not require an additional solution.
Anton Lebedev committedFeb 26, 2022 Configuration menu - View commit details
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Commits on May 19, 2022
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