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I have downloaded it and trained it on my server (4 GPUs, each GPU with 1 batchsize, 100k iters). I only used the GTA5 data to train the seg network (resnet101) and test on the cityscapes dataset (source only). I found the evaluation results is ~24% mIoU, which have a large gap compared to paper (39%). However, if I change the model from eval() to train() state in the evaluation, I got 34% mIoU. May I ask which state you have used in the paper? If it is eval() state, could you help us to find the potential issues?
Thanks.
The text was updated successfully, but these errors were encountered:
Hi. The work is excellent great.
I have downloaded it and trained it on my server (4 GPUs, each GPU with 1 batchsize, 100k iters). I only used the GTA5 data to train the seg network (resnet101) and test on the cityscapes dataset (source only). I found the evaluation results is ~24% mIoU, which have a large gap compared to paper (39%). However, if I change the model from eval() to train() state in the evaluation, I got 34% mIoU. May I ask which state you have used in the paper? If it is eval() state, could you help us to find the potential issues?
Thanks.
The text was updated successfully, but these errors were encountered: