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Result mismatch in coco metrics #6953
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👋 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. If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available. For business inquiries or professional support requests please visit https://ultralytics.com or email support@ultralytics.com. RequirementsPython>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started: git clone https://github.com/ultralytics/yolov5 # clone
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I had the same problem. |
@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. Lines 352 to 353 in 99de551
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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.
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?
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