[general]
name=RasterViz
qgisMinimumVersion=3.0
qgisMaximumVersion=3.99
description=Scientific raster visualization plugin for QGIS — styled after rasterio.show(), with interactive GUI controls for colormap selection, percentile/minmax stretch, pointed colorbar, discrete class mapping, RGB composite, and histogram analysis.
version=1.1.0
author=Defani Arman Alfitriansyah
email=defaniarman@gmail.com
about=RasterViz provides publication-quality raster visualization directly within QGIS, without requiring an external Python environment. The plugin replicates the rendering aesthetics of rasterio.show() through a fully interactive Qt5 GUI. Key capabilities include: single-band continuous rendering with configurable colormap and stretch (percentile, min-max, manual); discrete/classified raster rendering via per-class color and label assignment with automatic gridcode scanning; RGB three-band composite with independent per-band stretch; pointed colorbar with configurable geometry, orientation, and extend style (both, max, min, neither); coordinate tick formatting in DMS, DM, Decimal Degree, or native UTM/meter; real-time live preview backed by a cached NumPy array; and export to PNG (300 DPI), SVG, TIFF, and PDF. A standalone rendering module (raster_viz_demo.py) is also included for use outside QGIS in batch or notebook workflows. Built with PyQGIS, NumPy, Matplotlib (Qt5Agg backend), and PyQt5.
tracker=https://github.com/Defani/QRasterVIZ
repository=https://github.com/Defani/QRasterVIZ
homepage=https://github.com/Defani/QRasterVIZ
hasProcessingProvider=no
tags=raster, visualization, colormap, legend, colorbar, remote sensing, ndvi, rgb composite, stretch, mangrove, biomass, sentinel-2, landsat, classification, discrete
category=Raster
icon=icon.png
experimental=False
deprecated=False
changelog=Version 1.1.0 (2026): Initial public release. Includes Single-band continuous rendering, Discrete/classified rendering, RGB composite, customizable Pointed colorbar, coordinate tick formatting (DMS, DM, DD, UTM), and live preview via cached NumPy array. Export to PNG, SVG, TIFF, PDF supported.