You'll get tired of hearing how important data is to us—but honestly, it can make or break your development. In our case, we are going to simply use the same datasets that the original CycleGAN authors used in their development. This has two use cases: we can compare our results to theirs and we can take advantage of their small curated datasets.
So far, we've focused on just reviewing the structure of how we will solve the problem. As with every one of these chapters, we need to spend a few minutes collecting training data for our experiments. Replicate the directory structure with files, as seen as follows:
├── data │ ├── ├── docker │ ├── build.sh │ ├── clean.sh │ └── Dockerfile ├── README.md ├── run.sh ├── scripts │ └── create_data.sh ├── src │ ├──
We'll go and introduce the files you'll need to build so you can have a development environment and data to work with on CycleGAN.