Mean Average Precision (mAP) is a metric used to evaluate the accuracy of an object detection model by calculating the average precision across different classes. It combines the concepts of precision and recall, providing a comprehensive measure of how well a model identifies and classifies objects in images. mAP is particularly important in scenarios involving multiple classes and is widely used to assess the performance of models in tasks like image retrieval, detection, and classification.
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