Hi, I really thankful for you to share the code. In trainer_crossdomain.py the train function has set the eval_mask[:, int(0.40810811 * height):int(0.99189189 * height), int(0.03594771 * width):int(0.96405229 * width)] = 1 and I wonder how to get the float numbers? Also, I noticed that the structures of uncertainty_head and head are nearly the same. I don't understand the reason for this similarity. Looking forward to the reply and appreciate for the paper, your idea is inspiring. Best.
Hi, I really thankful for you to share the code. In trainer_crossdomain.py the train function has set the
eval_mask[:, int(0.40810811 * height):int(0.99189189 * height), int(0.03594771 * width):int(0.96405229 * width)] = 1and I wonder how to get the float numbers? Also, I noticed that the structures of uncertainty_head and head are nearly the same. I don't understand the reason for this similarity. Looking forward to the reply and appreciate for the paper, your idea is inspiring. Best.