srcnn

Super Resolution for Satellite Imagery
Applying super resolution strategies to sattelite imagery

Based on: https://arxiv.org/pdf/1501.00092.pdf

Usage

Train:

For training, training imagery should be stored under <data_path>/images. These images will automatically be cropped and processed for training/testing. There is an example image already in this directory and an easy way to accumulate more is using Google Maps.

python srcnn.py --action train --data_path data

Evaluate: python srcnn.py --action test --data_path data --model_path models/weights2.h5

Run: python srcnn.py --action run --data_path data --model_path models/weights2.h5 --output_path model_results