Closed CJHFUTURE closed 6 years ago
It actually depends on your applications and GPU memory.
If you have a GPU with 20GB, you can just set --loadSize 572 fineSize 512
for both training and test.
If you have a GPU with 10GB, you can train a model on cropped patches. In this case, you can set --loadSize 512 fineSize 256
for training, and set --loadSize 512 fineSize 512
for test. The model consumes much less memory during the test time, and the fully convolutional network can work for images with arbitrary sizes
Hi, could you confirm the flags and parameters to set for training at a resolution of 512x512? (Both image pairs are 512x512) And testing at the same and higher resolution.
Cheers:)