Using CGAN we have generated Realistic Faces from sketches, facades to buildings etc.
- Get datasets
- Copy the train-model.py in the directory of the data-set that you want to train.
- Run the train-model.py after installing all the required dependencies.
- Copy the final .h5 files generated in the webapp/models directory, named using the following nomenclature -
- facades2buildings_discriminator.h5
- facades2buildings_generator.h5
- maps2buildings_discriminator.h5
- maps2buildings_generator.h5
- scapes2city_discriminator.h5
- scapes2city_generator.h5
- sketch2faces_discriminator.h5
- sketch2faces_generator.h5
- Run the webapp/app.py file to start the flask app to run your models and provide input and generate output using a GUI.
- sketch.py was used to convert images to sketches to augment the training data.
- merge.py was used to merge the ground truth and the input image, as expected by the Neural Network.