DarkCoverage is an image analysis tool that helps you measure and visualize the coverage of dark or light areas in images using customizable thresholds and a grid-based approach.
Its usage is simple: Just run the program, load the image, and then use the sliders to specify appropriate threshold for each area.
- Load and analyze images with customizable number of rows and columns
- Set individual thresholds for each grid cell
- Color dark or light areas based on threshold values
- View real-time coverage percentage for each cell and overall image
- Compare with original image reference
- Save processed images
Installation:
pip install darkcoverageUsage:
darkcoverageor if Python is not included to path
darkcoverage.mainInstallation:
First, install uv if you haven't already (see uv docs for more information)
Then install DarkCoverage:
uv add darkcoverageOr install globally with uvx:
uvx darkcoverageUsage:
# If installed with uv add
uv run darkcoverage
# If installed with uvx
uvx darkcoverageInstallation:
-
Clone the repository:
git clone https://github.com/TZ387/darkcoverage.git cd darkcoverage -
Install the package:
pip install -e .
Usage:
python -m darkcoverage.mainInstallation:
-
Clone the repository:
git clone https://github.com/TZ387/darkcoverage.git cd darkcoverage -
Install dependencies and set up the project:
uv sync
Usage:
uv run python -m darkcoverage.main- Click "Load Image" to open an image file (such as Example.jpg in the main folder).
- Adjust the number of rows and columns using the row and column inputs in the sliders window
- Set threshold values for each cell using the sliders
- Toggle between "Color Dark Parts" and "Color Light Parts" to choose which areas to highlight
- View the coverage percentages for each cell and the total image
- Save the processed image with "Save Image"
In case something goes wrong, you can use reset image option.
DarkCoverage/
├── src/
│ └── darkcoverage/
│ ├── __init__.py
│ ├── main.py
│ ├── gui.py
│ ├── image_processing.py
│ └── widgets/
│ ├── __init__.py
│ ├── image_label.py
│ ├── reference_window.py
│ └── sliders_window.py
├── .gitignore
├── uv.lock
├── LICENSE
├── pyproject.toml
├── README.md
├── Demonstration.png
└── Example.jpg
- Python 3.8+
- PySide6
- Pillow
- NumPy
This project is licensed under the MIT License - see the LICENSE file for details.
