description: Explore Ultralytics YOLO metrics tools - from confusion matrix, detection metrics, pose metrics to box IOU. Learn how to compute and plot precision-recall curves.
keywords: 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](https://docs.ultralytics.com/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.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