wgenpatex

Wasserstein Generative Models for Patch-based Texture Synthesis

Code related to the paper https://arxiv.org/abs/2007.03408

• wgenpatex.py contains all the functions
• model.py contains the generative model architecture
• syntax python run_optim_synthesis.py target_image_path --options for running texture synthesis with image optimisation (Alg.1 from paper)
• syntax python run_cnn_synthesis.py target_image_path --options for learning an convolutional neural network texture generator (Alg.2 from paper) (GPU recommanded)

replace --options with any:

-w or --patch_size patch size -nmax or --n_iter_max max iterations of the algorithm -npsi or --n_iter_psi max iterations for psi -nin or --n_patches_in number of patches of the synthetized texture used at each iteration, -1 corresponds to all patches -nout or --n_patches_out number of patches of the target texture used at each iteration, -1 corresponds to all patches -sc or --scales number of scales used

--visu plot intermediate results --save save intermediate results in /tmp folder --keops' use keops package (speed-up)