Object Detection using Yolov3 results : yolo insert of multiple boxes for the same object

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ahcen aliouat
ahcen aliouat 2022-3-9
评论： ahcen aliouat 2022-4-29
Hello Matlabers,
I am usong YOLO v3 on matlab 2021a to recognize objects using YOLOv3 detector pretrained on COCO dataset.
the detector initiation is performed as:
name = 'tiny-yolov3-coco';
detector = yolov3ObjectDetector(name);
after the detection , I insert the bounding boxes using insertObjectAnnotation function
my problem is that the detector shows multiple boxes for the same object as shown in the image bellow
I am using grayscale image with replicated channels as Image=[gray, gray, gray]
the detection part is performed as follow:
[bboxes,scores,labels] = detect(detector,Image);
detected = insertObjectAnnotation(Image,'rectangle',bboxes,strcat(string(labels),{' - '},num2str(scores)));
what could be the problem and what are the possible solutions?
regards,

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采纳的回答

Vivek Akkala
Vivek Akkala 2022-4-28
Hi,
You can use selectStrongestBboxMulticlass to suppress the detections. Try lowering the "OverlapThreshold" of selectStrongestBboxMulticlass function. Following is the reference code:
[updatedBboxes, updatedScores, updatedClassNames] = selectStrongestBboxMulticlass(bboxes, scores, labels ,...
'RatioType', 'Union', 'OverlapThreshold', 0.3);
bboxes, scores and lables in the above code can be obtained from the detect(detector,image).
  1 个评论
ahcen aliouat
ahcen aliouat 2022-4-29
Hi vivek,
Thank you for the sugestition, it helps me.
I have tried it before and the problem was that it eliminate the two inserted boxes in many cases. Which significantly reduce the accuracy. but as you said , I have to lowerise the overlap threshold to get best performances.

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