# This file contains metadata for your plugin. Since 
# version 2.0 of QGIS this is the proper way to supply 
# information about a plugin. The old method of 
# embedding metadata in __init__.py will 
# is no longer supported since version 2.0.

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

[general]
name=dzetsaka : Classification tool
qgisMinimumVersion=3.0
description=Fast and Easy Classification plugin for Qgis with 11 ML algorithms + Auto-Install
version=4.2.2
author=Nicolas Karasiak
email=karasiak.nicolas@gmail.com

about=
      🎯 Powerful classification plugin supporting 11 machine learning algorithms:
      
      CORE: GMM, Random Forest, SVM, KNN
      ADVANCED: XGBoost, LightGBM, Extra Trees, Gradient Boosting, Logistic Regression, Naive Bayes, MLP
      
      🚀 NEW: Automatic dependency installation! No more manual pip commands - dzetsaka auto-installs scikit-learn, XGBoost, and LightGBM with one click.
      
      ⚡ Enhanced features: Hyperparameter optimization, sparse label handling, improved error handling, and GitHub issue integration.
      
      Very easy, fast, and powerful to use.
      For more information: https://github.com/nkarasiak/dzetsaka/

tracker=https://github.com/nkarasiak/dzetsaka/issues
repository=http://www.github.com/nkarasiak/dzetsaka

# End of mandatory metadata

# Recommended items:

# Uncomment the following line and add your changelog:
changelog=
    4.2.2
      * 🐛 FIX: Fixed import errors for splitTrain and trainAlgorithm class names
      * 🐛 FIX: Fixed progress_bar.progressBar attribute error (corrected case to ProgressBar)
      * 🐛 FIX: Restored missing toolbar icons by fixing Qt resources import
      * 🐛 FIX: Fixed incorrect resource path in sieve_area.py 
      * 🧹 ENHANCED: Applied ruff linting fixes and improved code quality
      * 📝 ENHANCED: Added proper docstrings to sklearn fallback classes
      * 🔧 ENHANCED: Better exception chaining for improved debugging
    4.2.0
      * 🎯 NEW: 7 additional machine learning algorithms - XGBoost, LightGBM, Extra Trees, Gradient Boosting, Logistic Regression, Naive Bayes, MLP
      * 🚀 NEW: Automatic dependency installation system - one-click install of scikit-learn, XGBoost, LightGBM
      * ⚡ NEW: Automatic hyperparameter optimization with cross-validation grid search for all algorithms
      * 🔧 NEW: Smart sparse label handling - automatically handles missing class labels (e.g., 0,1,3)
      * 📊 NEW: GitHub issue integration - automatic error reporting templates with system info
      * 🎨 IMPROVED: Better log levels (INFO vs WARNING) and more informative progress messages
      * 🐛 FIX: Resolved parameter delegation issues for XGBoost/LightGBM wrappers
      * 🐛 FIX: Fixed model serialization/pickling for new wrapper classes
      * 📈 ENHANCED: Real-time pip installation progress with detailed logging
      * 📝 ENHANCED: Comprehensive error handling with specific exception types and user guidance
    4.1.0
      * Major code refactoring and optimization of scripts/mainfunction.py
      * Remove Hungarian notation prefixes (in/out) from parameter names with full backward compatibility
      * Significant memory optimizations for large multi-band image processing
      * Enhanced error handling with specific exception types and detailed error messages
      * Added comprehensive type hints and improved documentation
      * Broke down 1279-line method into focused, maintainable helper methods
      * Added configuration constants for better maintainability
      * Created parameter migration guide for smooth transition
      * All old parameter names remain functional with deprecation warnings
    4.0.0
      * Major version with comprehensive improvements
    3.70
      * Fix bug with new gdal import from osgeo
    3.64
      * add closing filter in the processing toolbox
    3.63
      * fix bug in train algorithm (split waspercent of train not of validation)
    3.62
      * fig bug when loading cursor was not removed after unsucessful learning.
    3.61
      * fix bug #19 with self.addAlgorithm(alg).
    3.6
      * Add confidence map in processing
      * Add median filter and shannon entropy
      * Fix bug with GMM confidence map
      * Move dzetsaka icons to extension toolbar

# Tags are comma separated with spaces allowed
tags=classification,machine learning,xgboost,lightgbm,random forest,svm,knn,neural network,auto-install,processing

homepage=http://www.github.com/nkarasiak/dzetsaka
category=Raster
icon=icon.png

# experimental flag
experimental=False

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

