Flow-Guided-Feature-Aggregation
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Question about calculation of mAP
Hi, I'm reading the code to calculate mAP. In the code: https://github.com/msracver/Flow-Guided-Feature-Aggregation/blob/master/lib/dataset/imagenet_vid_eval.py#L58 When calculating the AUC of precision over recall on one class, it seems like the code enforces the precision to be monotonic by bumping up some precision.
Is this the general method to evaluate mAP?