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Explore Ultralytics YOLO metrics tools - from confusion matrix, detection metrics, pose metrics to box IOU. Learn how to compute and plot precision-recall curves. Ultralytics, YOLO, YOLOv3, YOLOv4, metrics, confusion matrix, detection metrics, pose metrics, box IOU, mask IOU, plot precision-recall curves, compute average precision

Reference for ultralytics/utils/metrics.py

!!! note

Full source code for this file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/metrics.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/metrics.py). Help us fix any issues you see by submitting a [Pull Request](/help/contributing/) 🛠️. Thank you 🙏!

::: ultralytics.utils.metrics.ConfusionMatrix




::: ultralytics.utils.metrics.Metric




::: ultralytics.utils.metrics.DetMetrics




::: ultralytics.utils.metrics.SegmentMetrics




::: ultralytics.utils.metrics.PoseMetrics




::: ultralytics.utils.metrics.ClassifyMetrics




::: ultralytics.utils.metrics.box_area




::: ultralytics.utils.metrics.bbox_ioa




::: ultralytics.utils.metrics.box_iou




::: ultralytics.utils.metrics.bbox_iou




::: ultralytics.utils.metrics.mask_iou




::: ultralytics.utils.metrics.kpt_iou




::: ultralytics.utils.metrics.smooth_BCE




::: ultralytics.utils.metrics.smooth




::: ultralytics.utils.metrics.plot_pr_curve




::: ultralytics.utils.metrics.plot_mc_curve




::: ultralytics.utils.metrics.compute_ap




::: ultralytics.utils.metrics.ap_per_class