I am wondering if there is a way to extract the confidence score associated with the predicted masks.
I am aware that I can extract the logits (described below) and pass them through a softmax layer to get confidence for each pixel, but I get very low values. Do you suggest any other way?
model = init_model(cfg, checkpoint_file, 'cuda:0')
result = inference_model(model, image)
for i in range(len(classes)):
seg_logits = result.seg_logits.data[i]
prob = F.softmax(seg_logits, dim=1)
Hello,
I am wondering if there is a way to extract the confidence score associated with the predicted masks. I am aware that I can extract the logits (described below) and pass them through a softmax layer to get confidence for each pixel, but I get very low values. Do you suggest any other way?
Thank you for your attention!