The mAP evaluation metric in object detection combines accuracy and recall.

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."