mAP Scores as Performance Metrics
Learn how can we evaluate performance of our model.
The mAP is used in object detection to compare the performance of a model. It combines two scores, precision and recall, to calculate how our model performs with respect to FN and FP.
How YOLO calculates TPs and FPs?
In object detection tasks performed by YOLO, evaluating the performance of the model involves concepts of true positives (TPs) and false positives (FPs). Here are some definitions of these concepts:
True positives (TPs): A true positive is an instance where the model correctly predicts the object—that is, the predicted bounding box correctly identifies and localizes an object in the image.
False positives (FPs): ...
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