ThemAP(mean Average Precision) metric in object detection combinesprecisionandrecall, not accuracy and recall. mAP is calculated by averaging the Average Precision (AP) across all classes in a dataset. Precision measures how many predicted positives are correct, while recall measures how many actual positives are identified. Accuracy, on the other hand, is a general metric for classification tasks and is less suitable for object detection where class imbalance and localization are important.
Exact Extract from HCIP-AI EI Developer V2.5:
"mAP evaluates object detection performance by considering both precision and recall across all classes, providing a balanced measure of detection accuracy and completeness." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Object Detection Metrics