DuFanXin / deep_residual_unet

Keras implementation of Road Extraction by Deep Residual U-Net article

Keras implementation of Deep Residual U-Net

The architecture was inspired by Road Extraction by Deep Residual U-Net

Overview

Data

Data should be prepared in the PASCAL VOC annotation way. For more information see docsting of PASCALVOCIterator class (utils.py)

Pre-processing

For preprocessing you could use standart keras utils for image preprocessing (keras.preprocessing.image)

Model

The architecture of the model based on the Road Extraction by Deep Residual U-Net. Image below illustrates it.

How to use

Train

In order to train model you could use train.py file. First of all you need to specify input_shape, dataset_folder and classes variables and then run train.py

Dependencies

This implementation depends on following libraries:

• Tensorflow
• Keras == 2.1.2 (probably >= 2.1.2)