Implementing mean Average Precision (mAP) for Object Detection in PyTorch
mAP (mean Average Precision) is a standard metric for evaluating object detectors. It summarizes precision–recall tradeoffs across cateegories, optionally averaged over multiple IoU thresholds. Precision = TP / (TP + FP) Recall = TP / (TP + FN) AP (per class) = area under the precision–recall curve...