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ContExt is a desktop application for image processing, contour extraction, interpolation, and sparse or adaptive mesh generation for numerical analysis workflows.
This project uses Python, a local .venv virtual environment, and dependencies defined in pyproject.toml.
The graphical interface is implemented with DearPyGUI, which uses platform graphics APIs (DirectX 11 on Windows, Metal on macOS, OpenGL 3 on Linux, and OpenGL ES on Raspberry Pi 4). Make sure the required graphics drivers are available on the target machine.
python3 -m venv .venv
source .venv/bin/activateOn Windows:
.venv\Scripts\Activate.ps1python3 -m pip install --upgrade pip
python3 -m pip install -e .If you prefer a compatibility file instead of editable installation:
python3 -m pip install -r requirements.txtUse the platform-specific build scripts in the project root. Each script creates a distributable artifact in release/.
bash ./build-macos.sh
Creates:
release/ContExt-macos-<arch>.app.zip
By default the macOS build uses the current machine architecture (arm64 or x64). You can override it with:
CONTEXT_TARGET_ARCH=arm64 bash ./build-macos.sh
or, if you have a universal2-compatible Python environment and dependencies:
CONTEXT_TARGET_ARCH=universal2 bash ./build-macos.sh
.\build.cmd
Creates:
release\ContExt-windows-x64.zip
bash ./build.sh
Creates:
release/ContExt-linux-x64.tar.gz
These first-step builds are unsigned. macOS and Windows may show security warnings when opening the application.
To execute the software run either command below:
python3 -m context
or
python3 main.py
- Import a large range of image formats
- Apply multiple image processing filters
- Extract contours with configurable approximation options
- Interpolate contours before export or meshing
- Generate sparse or adaptive meshes
You can download the binaries for each operating system on the Releases tab. Tagged releases publish the following artifacts:
ContExt-macos-<arch>.app.zipContExt-windows-x64.zipContExt-linux-x64.tar.gz
You can open a new issue or request a feature here. If you want to contribute to the project, see our contribution guideline.
Read our Code of Conduct.
This project is distributed under the GNU GENERAL PUBLIC LICENSE V3.0 and is registered with INPI (National Institute of Industrial Property).
Special thanks to professor Neyva Romeiro and the other professors at LabSan and Universidade Estadual de Londrina.





