Open gnoya opened 5 years ago
@gnoya Hi,
./darknet detector map data/obj.data yolo-obj.cfg backup\yolo-obj_9000.weights
At the end you will see 11 values of Precision and Recall for each class. So you can build PR-curve for each class by using these 11 points.
Don't use command detector recall
@AlexeyAB I randomly choose this issue to report a likely bug. when using detector map, I can get a mAP, and APs on each class. when using detector map -points 11, I will get a lower mAP, and lower APs on each class. when using detector map -points 21, the mAP and APs increase slightly. what's weird. Please try on your local machine with any cfg and weights file.
Hi, I'm testing my detector and I want to get the precision-recall curve (PR Curve) and I had some questions:
3070 7356 7715 RPs/Img: 3.51 IOU: 77.85% Recall:95.35%
Does that mean that from 7715 objects in the dataset, I got 7356 with more than 50% IoU?. Is there anyway to check the precision of those detections using this function (so I could get the PR curve)?
Thank you!