The Automated Drone Image Analysis Tool (ADIAT) provides a platform through with algorithm can be used to programmatically identify areas of interest in a set of image The primary use case for this tool is to aid in the analysis of images taken by UAVs during Search and Rescue Operations.
This tool was developed by Texas Search and Rescue (TEXSAR) as an open source project for the SAR community.
For more information about this project or to download the Windows Installer, please visit: https://www.texsar.org/automated-drone-image-analysis-tool/
- Leverages Color Detection capabilities provided by OpenCV (https://opencv.org/)
- UI build on QT_ Framework (https://www.qt.io/)
First create and activate a vitual environment working development environment Create Environment::
python -m venv <environment name>
Activate Environment (Windows)::
<environment name>\Scripts\activate
Activate Environment (Mac/Linux)::
source <environment name>/bin/activate
From the activated environment, install all dependencies::
pip install -r requirements.txt
pip install -r requirement-dev.txt
Once done, you can run the application like this::
python app
In order to ease the development process, the Qt Creator project app.pro is
provided. You can open it to edit the UI files or to manage resources.
UI files and resources can be built like this
python setup.py build_res
Note that this command is automatically run before running sdist and
bdist_app commands.
You can generate a compiled application so that end-users do not need to
install anything. You can tweak some settings on the app.spec file. It can
be generated like this
python setup.py bdist_app
If you are interesting in contributing to this project by either enhancing an existing capability or adding new features/algorithms please reach out to us at charlie.grove@texsar.org