Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch
This is a Pytorch implementation of cascaded refinement networks to synthesize photographic images from semantic layouts. Now the pretrained model and codes for training the network from scratch are available for 256×512 resolution. Thanks to Qifeng Chen for his tensorflow implementation which helped a lot in developing this pytorch version.
Testing
- Download this package and keep all the subsequent mentioned files in the same folder.
- Download the pretrained VGG19 Net from VGG19
- Download the pretrained weights for the CRN network for 256×512 CRN
- Keep the mode=test and mention the semantic image name to be tested in the Cascadaed_Network_LM_256.py
- The synthesized images will be saved in current folder.
Training
- Follow steps 1 to 3 from the testing steps.