ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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Result mismatch in coco metrics #6953

Closed purvang3 closed 2 years ago

purvang3 commented 2 years ago

Search before asking

YOLOv5 Component

Validation

Bug

I see results are not same for mAP@0.50 and mAP@0.50:0.95 during training after each epoch. I have made changes in val.py accordingly as I am using "xywh" format for bboxes.

I have commented line

box[:, :2] -= box[:, 2:] / 2 # xy center to top-left corner as my gt in xywh format.

Screen Shot 2022-03-11 at 12 54 35 PM

Environment

YOLOv5 🚀 v6.0-144-gc9a46a6 torch 1.10.2 CUDA:0 (NVIDIA RTX A4000, 16116MiB)
os : Ubuntu 18.04

Minimal Reproducible Example

make save_json in val.run=True and start training.

Additional

No response

Are you willing to submit a PR?

github-actions[bot] commented 2 years ago

👋 Hello @purvang3, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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Python>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

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cd yolov5
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glenn-jocher commented 2 years ago

@purvang3 yes mAP mismatch with pycocotools is a known issue, and there's actually an open competition to solve it in https://github.com/ultralytics/yolov5/issues/2258

We also have a few PRs related to mAP updates from users that you could try:

codingonion commented 2 years ago

@purvang3 yes mAP mismatch with pycocotools is a known issue, and there's actually an open competition to solve it in #2258

We also have a few PRs related to mAP updates from users that you could try:

* [Improve mAP0.5-0.95 #6787](https://github.com/ultralytics/yolov5/pull/6787)

* [Fix mAP bug at a higher conf #6813](https://github.com/ultralytics/yolov5/pull/6813)

I had the same problem. test.py in v4.0、v5.0 is OK. val.py in v6.0、v6.1 is not OK. Please see blow. v5 0 v6 0

glenn-jocher commented 2 years ago

@dotnet-rs-py we have a warning in place to advise users of incorrect settings. mAP should be calculated at --conf 0.0 for best results, we compute at --conf 0.001 for significant speed improvements at near identical results. Anything above that will not allow for a full integration of the PR curve from 0 to 1, which will result in incorrect mAP.

https://github.com/ultralytics/yolov5/blob/99de551f979f6aca1f817504831c821cff64b5fd/val.py#L352-L353

github-actions[bot] commented 2 years ago

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

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