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This repository has been archived by the owner on Jul 11, 2022. It is now read-only.
Thank you for sharing. I am interesting about this work. While I use the YOLOv3 https://github.com/ultralytics/yolov3/ as the object detector.
I can generate the salience map when the image only have one object with a category, like the followings.
While it can't work when the image contain multiple objects of a categories like the persons in this image
The code compute the score I revised it as
'conf = max([iou(target_box, box)*conf], default=0)'
Could you give me some advice?
The text was updated successfully, but these errors were encountered:
Thank you for sharing. I am interesting about this work. While I use the YOLOv3 https://github.com/ultralytics/yolov3/ as the object detector. I can generate the salience map when the image only have one object with a category, like the followings.
While it can't work when the image contain multiple objects of a categories like the persons in this image
The code compute the score I revised it as 'conf = max([iou(target_box, box)*conf], default=0)'
Could you give me some advice?
I applied on Yolo v3 and don't appear the problem you said.
Thank you for sharing. I am interesting about this work. While I use the YOLOv3 https://github.com/ultralytics/yolov3/ as the object detector.
I can generate the salience map when the image only have one object with a category, like the followings.
While it can't work when the image contain multiple objects of a categories like the persons in this image
The code compute the score I revised it as
'conf = max([iou(target_box, box)*conf], default=0)'
Could you give me some advice?
The text was updated successfully, but these errors were encountered: