CycleGAN_emoji
Swap Apple-Windows styles emojis using CycleGAN
This is based on an assignment of CSC321-Winter-2018, University of Toronto.
The task
In this assignment, you’ll get hands-on experience coding and training GANs. This assignment is divided into two parts: in the first part, we will implement a specific type of GAN designed to process images, called a Deep Convolutional GAN (DCGAN). We’ll train the DCGAN to generate emojis from samples of random noise. In the second part, we will implement a more complex GAN architecture called CycleGAN, which was designed for the task of image-to-image translation (described in more detail in Part 2). We’ll train the CycleGAN to convert between Apple-style and Windows-style emojis.
Dependencies
- PyTorch (developed in 1.11.0)
- torchvision (developed in 0.12.0)
Inventory
config.py: configuration settings for training.model.py: model definitions.loader.py: data loader.train.py: training script.test.py: perform inference using trained model.
Results
The following are some random inference results on the test dataset, using pre-trained weights trained after 100 epochs.
The first row contains Apple-to-Windows style-transferred emojis, and the 2nd row the reverse transfers.
