Understanding COCO evaluation “maximum detections”
问题 I started using the cocoapi to evaluate a model trained using the Object Detection API. After reading various sources that explain mean average precision (mAP) and recall, I am confused with the "maximum detections" paramter used in the cocoapi. From what I understood (e.g. here, here or here), one calculates mAP by calculating precision and recall for various model score thresholds. This gives the precision-recall curve and mAP is calculated as an approximation to the area under this curve.