RGB-to-NDVI-conversion dataset

Dataset for the article: Evaluating Generalization of Methods for Artificially Generating NDVI from UAV RGB Imagery in Vineyards

A full description of the article can be found at MDPI Remote Sensing: https://www.mdpi.com/2072-4292/17/3/512

As well as the base data for training Pix2Pix architectures presented on GitHub.

This data repository contains:

p2p_data.rar which are the preprocessed chips which were used to train and evaluate the Pix2Pix models on. In this folder:

256x256 and 512x512 chips each in individual folders per sensor:

ms_512 

ms_256

rgb_512

ms_256

256x256: ms contains only training useful chips, rgb_256 contains all the test chips from can2023 and btg2021 as well

A=RGB

B=NDVI 

AB aligned A+B

512x512: Each folder contains the structure that Pix2Pix expects:

A for 3band imgs, B for NDVI

train_A/test_A/val_A -> RGB or msRGB chips from BTG2022

train_B/test_B/val_B -> NDVI chips from BTG2022

test_2021_A -> msRGB chips from BTG2021

test_2023_A -> RGB chips from CAN2023

*_B -> NDVI chips

orthos.rar, used in the earliest stages to create chips, and used for evaluation again later.

canyelles: RGB, ndvi, chm, dem, dsm

btg2021, ms, ndvi, chm, dem, dsm

btg2022, ms, RGB, ndvi, chm, dem, dsm

preprocessed.rar:

Input files for the evaluation code, after aligning rasters, reconstructing chips to orthos