I have trained a face detection model, and ready to use it to predict object and the coorsponding bounding box. I have some questions about the predictions. Here is what I do now:
- The prediction is a vector of 6, which is
[top, left, bottom, right, background_score, face_score].
- Get the
confidenceby applying softmax to
confidenceis the softmax result of face score.
- Sort the whole predictions by
confidenceand keep only the top 1000.
- Filter the 1000 prediction by a
confidence threshold, 0.9 or higher.
none-maximum suppressionand get the final bounding boxes.
I wander if this is the right way to do it. If it is, I found the 2 variable
0.9 is very hard to pick. Is there a better way to chose the 2 value?