# This file contains metadata for your plugin.

# This file should be included when you package your plugin.# Mandatory items:

[general]
name=Supervised Classifier
qgisMinimumVersion=3.0
description=A plugin to classify selected raster file with reference
version=0.2
author=Mirjan Ali Sha
email=mastools.help@gmail.com

about=Supervised Classifier: A plugin to classify selected raster file with reference.. The Supervised Classifier Plugin for QGIS is a powerful tool designed to facilitate the classification of satellite images using unsupervised learning algorithms. This plugin provides an easy-to-use interface for loading satellite images and selecting from a variety of supervised classification methods, including "Minimum Distance", "Random Forest", "SVM" and KNN. Also working on "Maximum Likelihood" algorithm as well. Key Features: 1. User-Friendly Interface: Intuitive dialog for selecting classification parameters. 2. Multiple Algorithms: Support for "Minimum Distance" (most effective), "Random Forest", "SVM" and "KNN" (not good) algorithms. 3. Seamless Integration: Directly integrates with QGIS, allowing for easy access and visualization of classification results. 4. Flexible: Handles different types of satellite images and provides robust classification results. This plugin is ideal for remote sensing professionals, GIS analysts, and researchers looking to perform efficient and accurate unsupervised classification of satellite imagery within the QGIS environment. To use this Tool follow the below steps: 1. Click on the tool or chose "Raster" menu --> "MAS Raster Processing" menu item --> "Supervised Classifier" option. 2. Select 'Stack Image' or Image as Input and select output folder name. 3. Select classification method. 4. Adjust all parameters according to your needs. Select the field of the Reference Shapefile which has the labels for the classification and check mark on "Want to save the trained model?" if you wants save the trained model (except "Minimum Distance" model). Select the "No of Iterations:" to trained the model (except "Minimum Distance" model). 5. Decide do you wants to open the output or not. 6. Click on "Classify" button. **Note: After installation make sure the following points; 1. Check Mark the Installed plugins (under 'Manage and Install Plugins...' menu). 2. Check Mark 'MAS Raster Processing' toolbar (by right click on toolbar). Issues (please take a look): [ModuleNotFoundError: No module named 'sklearn' #1](https://github.com/Mirjan-Ali-Sha/supervised_classifier/issues/1)



tracker=https://github.com/Mirjan-Ali-Sha/supervised_classifier/issues
repository=https://github.com/Mirjan-Ali-Sha/supervised_classifier
# End of mandatory metadata

# Recommended items:

hasProcessingProvider=no
# Uncomment the following line and add your changelog:
# changelog=1. Fixed "Failed to classify the image: object of type 'numpy.int64' has no len()" error. 2. Improve KNN algo.

# Tags are comma separated with spaces allowed
tags=remote sensing, raster, processing, image classification, supervised classification

homepage=https://github.com/Mirjan-Ali-Sha/supervised_classifier/wiki
category=Raster
icon=icon.png
# experimental flag
experimental=False

# deprecated flag (applies to the whole plugin, not just a single version)
deprecated=False

# Since QGIS 3.8, a comma separated list of plugins to be installed
# (or upgraded) can be specified.
# Check the documentation for more information.
# plugin_dependencies=

Category of the plugin: Raster, Vector, Database or Web
# category=

# If the plugin can run on QGIS Server.
server=False

