[general]
name=Magic Georeferencer
qgisMinimumVersion=3.22
description=AI-powered automatic image georeferencing using MatchAnything deep learning model
version=1.1.0
author=Magic Georeferencer Team
email=contact@example.com

about=Automatically georeference maps, aerial photos, and sketches using the MatchAnything deep learning model. Simply navigate to the approximate location and let AI find the matching features.
    .
    Features:
    - Zero manual GCP placement - fully automated
    - Cross-modality support (maps to aerial, aerial to maps, sketches to maps)
    - Progressive multi-scale refinement for improved accuracy
    - GPU acceleration with automatic CPU fallback
    - Confidence-based match filtering
    .
    Requirements:
    - QGIS 3.22 or higher (Windows, macOS, Linux)
    - Python 3.9+ (bundled with QGIS)
    - 8 GB RAM minimum, 16 GB recommended
    - ~2 GB disk space for model cache
    - Optional: NVIDIA GPU with CUDA for faster processing
    .
    External Dependencies (auto-installed on first run):
    - PyTorch >= 2.0.0 and TorchVision >= 0.15.0 (deep learning framework)
    - Transformers >= 4.30.0 (HuggingFace model support)
    - OpenCV >= 4.8.0 (image processing)
    - SciPy >= 1.9.0 (scientific computing)
    .
    The plugin automatically downloads the AI model weights (~400 MB) from HuggingFace on first use.
    .
    Platform Support: Works on Windows, macOS, and Linux. GPU acceleration requires NVIDIA CUDA-capable GPU (optional, CPU fallback available).
    .
    License: Apache License 2.0

tracker=https://github.com/FungoBungaloid/georefio/issues
repository=https://github.com/FungoBungaloid/georefio
tags=georeferencing, machine learning, AI, automation, image matching, deep learning, raster

homepage=https://github.com/FungoBungaloid/georefio
category=Raster
icon=icon.png
experimental=True
deprecated=False

changelog=
    1.0.0 - Initial release
        - AI-powered automatic georeferencing
        - MatchAnything EfficientLoFTR model integration
        - GPU and CPU support with auto-detection
        - Progressive multi-scale refinement
        - Quality presets (Strict/Balanced/Permissive)
        - Multi-source basemap support (OSM, ESRI)
        - Comprehensive documentation

credits=Built on MatchAnything by He et al. (2025)
    https://github.com/zju3dv/MatchAnything
    .
    Uses HuggingFace Transformers for model management
    Basemap tiles from OpenStreetMap and ESRI
    .
    Co-developed using Claude Code by Anthropic
