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Hello,
I have been using the YOLO face detection dataset and came across an interesting observation regarding the landmark confidence scores.
I noticed that the confidence scores for landmarks are marked as 2.0 in the labeled data.
Typically, I understand that confidence scores are represented between 0 and 1, so I am curious about the rationale or intent behind this particular notation.
Is this a reflection of a specific rule or preprocessing method in the dataset, or is there another reason for this notation?
I would greatly appreciate any clarification on this matter.
The text was updated successfully, but these errors were encountered:
From what I understand, the format of data is like this. 0,cx,cy,w,h,kx1,ky1,v1,kx2,ky2,v2.. .Here 2 is used to represent the visibility , if its is 0 then it means the keypoint is not visible. 2 means visible. While calculating the loss, only those keypoints with visiblility 2 is taken
Hello,
I have been using the YOLO face detection dataset and came across an interesting observation regarding the landmark confidence scores.
I noticed that the confidence scores for landmarks are marked as 2.0 in the labeled data.
Typically, I understand that confidence scores are represented between 0 and 1, so I am curious about the rationale or intent behind this particular notation.
Is this a reflection of a specific rule or preprocessing method in the dataset, or is there another reason for this notation?
I would greatly appreciate any clarification on this matter.
The text was updated successfully, but these errors were encountered: