A Tensorflow implementation of Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks using Eager Execution, tf.keras.layers, and tf.data.
Requirements:
- Tensorflow 1.11.0
- Python 3.6
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md
├── data
│ └── raw <- Raw data before any processing.
│
├── saved_models <- Checkpointed models and tensorboard summaries.
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
└── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
│
├── train.py <- Run this to train.
│
├── test.py <- Run this to test.
│
├── pipeline <- Code for downloading or loading data
│ ├── data.py
│ └── download_data.py
│
├── options <- Files for command line options
│ └── base_options.py
│
├── models <- Code for defining the network structure and loss functions
│ ├── __init__.py <- model helper functions
│ ├── network.py
│ ├── cyclegan.py
│ └── losses.py
│
└── utils <- Utility files, including scripts for visualisation
└── image_history_buffer.py
Project based on the cookiecutter data science project template. #cookiecutterdatascience