Generate cartoon faces with variational auto-encoders. Built with TensorFlow 2.0-beta1, trained 4 epochs with GTX1060 3GB and took 2 hours. Also in this software, you shall see a great use of TensorBoard. Here are results generated with random bottlenecks;

You can download pre-trained models from the directory named models

You can download the dataset that i used from here

Bottom, you can see files, classes in files, functions in classes and what those functions do. My class names are from TV Show named 'How I Met Your Mother', it is like this because i kinda like use the names of show characters on my code :)

• load_image: loads image, no label
• read_all_data: gets all the paths and labels, saves it as npy

Summary: Create tensorflow dataset object with map

• encoder_model: create encoder model
• decoder_model: create decoder model
• encode: gets bottleneck and split into two(mean, logvar)
• decode: gets reparameterized input and put it into decoder
• reparameterize: gets mean and logvar and reparameterize them
• generate_sample: creates random input for decoder and generate image by through decoder
• log_normal_pdf: sub loss function
• compute_loss: do everything and calculate loss
• save: save encoder and decoder
• train_step: combine those things, and optimize model by through self.optimizer

Summary: Create model structure, loss, optimizer and simple train step

• save_images_to_tensorboard: gets regenereted and real images, generate some from random and save to tensorboard
• train_model: train model by through barney and marshall, use 'save_images_to_tensorboard' to test it

Summary: Train model

[WARNING] This project still in developing faze which means that i will add more algorithms, data structures and stuff like that.

Please ask if you have questions :)