RFDNet Super Resolution
Keras Implementation of the paper Residual Feature Distillation Network for Lightweight Image Super-Resolution.
Getting Started
- Clone the repository
Prerequisites
- Tensorflow 2.2.0+
- Python 3.6+
- Keras 2.3.0
- PIL
- numpy
pip install -r requirements.txt
Running
Training
-
Train RFDNet
python main.py
-
Test RFDNet
python test.py
Usage
Testing
usage: test.py [-h] [--test_path TEST_PATH] [--gpu GPU]
[--weight_test_path WEIGHT_TEST_PATH] [--filter FILTER]
[--feat FEAT] [--scale SCALE]
optional arguments:
-h, --help show this help message and exit
--test_path TEST_PATH
--gpu GPU
--weight_test_path WEIGHT_TEST_PATH
--filter FILTER
--feat FEAT
--scale SCALE
Result
Input - Low Res | Bilinear | Output High Res |
---|---|---|