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GeoAI

QGIS Plugin GitHub

A QGIS plugin that brings the geoai models into dockable panels (Moondream VLM, segmentation training and inference, SamGeo), so you can keep QGIS as your main workspace while experimenting with geospatial AI.

Quick Start

Video Tutorials

Installation Tutorial

GeoAI QGIS Plugin Installation on Linux and Windows

Usage Tutorial

Full Usage Tutorial for the GeoAI QGIS Plugin

GeoAI QGIS Plugin Short Demo

Features

Each tool lives inside a dockable panel that can be attached to either side of the QGIS interface, so you can keep layers, maps, and models visible simultaneously.

Moondream Vision-Language Model Panel

Segmentation Panel (Combined Training and Inference)

SamGeo Panel (Segment Anything Model)

GPU Memory Management

Installation

1. Set Up the Environment

Installing the GeoAI QGIS plugin can be challenging due to the complicated PyTorch/CUDA dependencies. Conda or mamba might take a while to resolve dependencies, while pip might fail to install them properly. Using pixi is recommended to avoid these issues.

1. Install Pixi

Linux/macOS (bash/zsh):

curl -fsSL https://pixi.sh/install.sh | sh

Windows (PowerShell):

powershell -ExecutionPolicy Bypass -c "irm -useb https://pixi.sh/install.ps1 | iex"

Close and re-open your terminal, then confirm with pixi --version.

2. Create a Pixi Project

pixi init geo
cd geo

3. Configure pixi.toml

Open pixi.toml in the geo directory and replace its contents with one of the configurations below depending on your system. If you have an NVIDIA GPU, run nvidia-smi to check your CUDA version.

GPU with CUDA 12.x:

[workspace]
channels = ["https://prefix.dev/conda-forge"]
name = "geo"
platforms = ["linux-64", "win-64"]

[system-requirements]
cuda = "12.0"

[dependencies]
python = "3.12.*"
pytorch-gpu = ">=2.7.1,<3"
qgis = "3.42.*"
pyqt = "5.15.*"
geoai = ">=0.24.0"
segment-geospatial = ">=1.2.0"
sam3 = ">=0.1.0.20251211"
libopenblas = ">=0.3.30"

GPU with CUDA 13.x:

[workspace]
channels = ["https://prefix.dev/conda-forge"]
name = "geo"
platforms = ["linux-64", "win-64"]

[system-requirements]
cuda = "13.0"

[dependencies]
python = "3.12.*"
pytorch-gpu = ">=2.7.1,<3"
qgis = "3.42.*"
pyqt = "5.15.*"
geoai = ">=0.24.0"
segment-geospatial = ">=1.2.0"
sam3 = ">=0.1.0.20251211"

CPU only:

[workspace]
channels = ["https://prefix.dev/conda-forge"]
name = "geo"
platforms = ["linux-64", "win-64"]

[dependencies]
python = "3.12.*"
pytorch-cpu = ">=2.7.1,<3"
qgis = "3.42.*"
pyqt = "5.15.*"
geoai = ">=0.24.0"
segment-geospatial = ">=1.2.0"
sam3 = ">=0.1.0.20251211"
libopenblas = ">=0.3.30"

4. Install the Environment

From the geo folder:

pixi install

This step may take several minutes on first install depending on your internet connection and system.

5. Verify PyTorch + CUDA

If you have an NVIDIA GPU with CUDA, verify the installation:

pixi run python -c "import torch; print('PyTorch:', torch.__version__); print('CUDA available:', torch.cuda.is_available()); print('GPU:', (torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'None'))"

Expected output should look like:

If CUDA is False, check that nvidia-smi works and that your NVIDIA driver is up to date.

Request Access to SAM 3

To use SAM 3, request access at https://huggingface.co/facebook/sam3. Once approved, authenticate and download the model:

pixi run hf auth login
pixi run hf download facebook/sam3

Note: SAM 3 currently requires an NVIDIA GPU with CUDA support and will not run on CPU-only systems.

2. Install the QGIS Plugin

GeoAI is available in the official QGIS plugin repository:

  1. Launch QGIS: pixi run qgis.

  2. Go to Plugins > Manage and Install Plugins....

  3. Switch to the All tab, search for GeoAI, select it, and click Install Plugin.

If an error dialog appears after installation, click Close, toggle the checkbox next to the GeoAI plugin to enable it, close any subsequent error dialogs, and restart QGIS to reload the plugin.

Option B: Helper Script

git clone https://github.com/opengeos/geoai.git
cd geoai/qgis_plugin
python install.py
# Remove with:
python install.py --remove

This links or copies the plugin into your active QGIS profile. Re-run after pulling updates.

Option C: Manual Copy

Copy the qgis_plugin folder to your QGIS plugins directory:

3. Enable in QGIS

Launch QGIS (pixi run qgis), then go to Plugins > Manage and Install Plugins... and enable GeoAI. After updates, toggle the plugin off/on or restart QGIS to reload.

Usage

Moondream Vision-Language Model

Sample dataset: parking_lot.tif

  1. Click the Moondream button in the GeoAI toolbar (or GeoAI > Moondream VLM).

  2. Load a Moondream model (default: vikhyatk/moondream2).

  3. Select a raster layer or browse for an image file.

  4. Choose a mode:

    • Caption: Generate a description of the image.

    • Query: Ask a question about the image.

    • Detect: Detect objects by type (e.g. “building”, “car”).

    • Point: Locate specific objects.

  5. Click Run.

  6. Results are displayed and optionally added to the map. Save the output table or vector layer to reuse detections later.

Segmentation Panel (Create Data, Train, Inference)

Sample datasets:

  1. Download the sample datasets or prepare your own imagery and vector labels. Store them in a folder accessible to the pixi project.

  2. Click the Segmentation button in the GeoAI toolbar (or GeoAI > Segmentation).

  3. Use the tabs at the top of the panel to switch between:

    • Create Training Data: Select input raster and vector labels, configure tile size and stride, and export tiles to a directory.

    • Train Model: Select the images and labels directories, choose model architecture (U-Net, DeepLabV3+, etc.), configure training parameters, and start training.

    • Run Inference: Select input raster layer or file, specify the trained model path, configure inference parameters, run inference, and optionally vectorize the results.

SamGeo Panel (Segment Anything Model)

Sample datasets:

  1. Click the SamGeo button in the GeoAI toolbar (or GeoAI > SamGeo).

  2. In the Model tab:

    • Select the SAM model version (SamGeo3/SAM3, SamGeo2/SAM2, or SamGeo/SAM1).

    • Configure backend (meta or transformers) and device (auto, cuda, cpu).

    • Click Load Model to initialize the model.

    • Select a raster layer or browse for an image file and click Set Image.

  3. Choose a segmentation method:

    • Text Tab: Enter text prompts describing objects (e.g. “tree, building”).

    • Interactive Tab: Click Add Foreground Points / Add Background Points and click on the map, or click Draw Box and drag a rectangle, then click Segment by Points or Segment by Box.

    • Batch Tab: Add multiple points interactively or load from a vector file/layer.

  4. In the Output tab:

    • Select output format (Raster GeoTIFF, Vector GeoPackage, or Vector Shapefile).

    • For vector output, optionally enable regularization: check “Regularize polygons (orthogonalize)” and set Epsilon (simplification tolerance) and Min Area (filter small polygons).

    • Click Save Masks to export results.

Clear GPU Memory

Click the GPU button in the GeoAI toolbar to release GPU memory from all loaded models (Moondream, SamGeo, etc.) and clear the CUDA cache. Use this frequently when switching between large models to prevent out-of-memory errors.

Plugin Update Checker

Go to GeoAI > Check for Updates... to see if a newer version is available. Click Check for Updates to fetch the latest version info from GitHub, then Download and Install Update to install it. Restart QGIS to apply the update.

Supported Model Architectures (Segmentation)

The QGIS plugin supports any models available through PyTorch Segmentation Models, including:

Supported Encoders (Segmentation)

Supported SAM Models (SamGeo)

Troubleshooting

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Leafmap
QGIS Plugins
Video Tutorials