Light Weight Residual Dense Attention Net for Spectral Reconstruction

This is implementation of LWRDA Net "Light Weight Residual Dense Attention Net for Spectral Reconstruction from RGB Images by K.Uma et .2020"

Environment

1. Python 3.6.1
2. Anaconda 5.0.1
3. Ubuntu 16.04 or Windows10

How to setup the environment

Step 1

Unzip the downloaded folder

Step 2

Open the powershell or terminal

Step 3

$cd yourpathtoLightWeightModel

$pwd
> ~/LightWeightModel

$pip install --upgrade -r requirements.txt

How to test the model on your own imgaes

$python test.py --testImagePath=yourpathtoimages

Results

Data size	Data	MRAE	SSIM
400	Training Data	0.02372	0.9899
50	Validation Data	0.04497	0.9827
10	Testing Data1	0.05478	-
10	Testing Data2	0.04577	-

Reference

1. "Coordinate 2D Convolution layer"