radioviz 1.1.0
A tool to display and manipulate autoradiography grayscale images
Requires Python: >=3.8
Keywords: autoradiography, visualization

# RadioViz
RadioViz is a specialized tool designed for displaying and manipulating autoradiography grayscale images. This application provides a user-friendly interface to handle TIFF images, offering functionalities such as adjusting display levels, applying color maps, and analyzing intensity profiles.

[![pipeline status](https://code.europa.eu/kada/radioviz/badges/main/pipeline.svg)](https://code.europa.eu/kada/radioviz/-/commits/main) 

[![Latest Release](https://code.europa.eu/kada/radioviz/-/badges/release.svg)](https://code.europa.eu/kada/radioviz/-/releases) 

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## Table of Contents

- [Installation](#installation)
- [License](#license)
- [Features](#features)
- [Usage](#usage)
- [Authors](#author)
- [Contributions](#contributions)
- [Support](#support)
- [Acknowledgements](#acknowledgements)

## Installation

The package can be installed using pip. In this case, it is recommended to install the package in a separate virtual environment:

```bash
python -m venv radioviz
cd radioviz
source bin/activate
pip install radioviz 
```
If you prefer, you can also install the package and make it available system-wide using pipx instead of pip. This will allow the execution of the tool without starting the virtual environment.

```bash
pipx install radioviz 
```

## License

`radioviz` is distributed under the terms of the [EUPL-1.2](https://spdx.org/licenses/EUPL-1.2.html) license.

## Features
 - **Image Display**: Open and view TIFF images with options to adjust display levels and apply different color maps and interpolation methods.
 - **Profile Analysis**: Select and analyze intensity profiles across specified lines within an image. 
 - **Region Analysis**: Select and analyze intensity distribution of ROI.
 - **Automatic cropping**.

## Execute the application:

Either double click on the icon, or type ``radioviz`` from a terminal

## Usage
- **Open Image**: Navigate to the "File" menu and select "Open" to load a TIFF image. Recent files can be accessed from the "Open Recent" submenu.
- **Adjust Display**: Use the "Image Tools" dock to adjust levels or change the color map and interpolation of the displayed image.
- **Analyze Profiles**: Select the "Profile Tools" dock to add new profiles. Click "Add Profile" and select two points on the image to define the profile line.
- **Analyze Regions**: Use the "Region Tools" dock to select rectangular areas on the input image and calculate areas properties.


## Author
Developed by Antonio Bulgheroni (antonio.bulgheroni@ec.europa.eu).

## Contributions
Contributions are welcome! Please open an issue to discuss your ideas or submit a pull request with your changes.

The developers used [hatch](https://hatch.pypa.io/) as project manager. Do the following to start contributing to the project:

1. Ensure hatch is installed in your system. If not, we recommend to install it using pipx
2. Clone the RadioViz repository locally
    ``git clone https://code.europa.eu/kada/radioviz.git``
3. Enter the directory of the freshly cloned repo
    ``cd radioviz``
4. Create the development environment and start a shell using hatch
    ``hatch shell dev``
5. RadioViz developers adopted [pre-commit](https://pre-commit.com/) to assure high code quality. The first time you need to install the pre-commit hooks:
    ``pre-commit install --install-hooks -t pre-commit -t pre-push``
6. Start developing in your preferred IDE. 
7. Remember that RadioViz uses [conventional commit message](https://www.conventionalcommits.org/en/v1.0.0/). Please follow it. To commit changes you will also need a token with full repository access. Again refer to the [project maintainer](mailto:antonio.bulgheroni@ec.europa.eu). 

## Support
For any questions or support, please contact Antonio Bulgheroni at antonio.bulgheroni@ec.europa.eu.

## Acknowledgements
This tool was developed as part of the JRC projects on autoradiography analysis.