I’m trying to evaluate MoveNet.SinglePose.Lightning using the COCOEval API.
However, I do not know how to calculate the score to use for evaluation.
Referring to the Results Format page, one score must be set for each inference result for the evaluation of keypoint detecition.
And this score is the instance-level confidence of the object.
[{
"image_id": int,
"category_id": int,
"keypoints": [x1,y1,v1,...,xk,yk,vk],
"score": float,
}]
But, MoveNet.SinglePose.Lightning outputs the confidence for each keypoint and not the instance-level confidence.
ref. The model card
Outputs
A float32 tensor of shape [1, 1, 17, 3].
The first two channels of the last dimension represents the yx coordinates (normalized to image frame, i.e. range in [0.0, 1.0]) of the 17 keypoints (in the order of: [nose, left eye, right eye, left ear, right ear, left shoulder, right shoulder, left elbow, right elbow, left wrist, right wrist, left hip, right hip, left knee, right knee, left ankle, right ankle]).
The third channel of the last dimension represents the prediction confidence scores of each keypoint, also in the range [0.0, 1.0].
How can I calculate the score or do the evaluation?
