This repository provides an implementation of semantic segmentation for road networks using PyTorch and the U-Net architecture. It focuses specifically on processing aerial images from the Massachusetts dataset.
The Massachusetts dataset consists of aerial images captured from various locations in Massachusetts, USA. It includes high-resolution images labeled with pixel-level annotations for road networks.
To use this codebase, you need to obtain the Massachusetts dataset separately. You can find the dataset and its corresponding annotations on this link.
Image---Mask
Contributions to this project are welcome. If you find any issues or have suggestions for improvements, please open a new issue or submit a pull request.
This project is licensed under the MIT License.