lee-zq/3DUNet-Pytorch: 3DUNet implemented with pytorch - GitHub
3) Testing 3DUNet. run test.py Please pay attention to path of trained model in test.py. (Since the calculation of the 3D convolution operation is too large, I use a sliding window to block the input tensor before prediction, and then stitch the results to get the final result.
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