Mean average precision (mAP) is a metric used to evaluate the accuracy of object detection systems by measuring how well the predicted bounding boxes align with the actual objects in an image. It considers both the precision and recall of the detections across different classes and thresholds, providing a comprehensive view of performance. By averaging the precision scores at different recall levels, mAP helps gauge the overall effectiveness of an object detection algorithm in recognizing and localizing multiple objects.
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