We use the Open Source Computer Vision Library OpenCV with Cascade Classifier features to detect and track the target.
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Detect the host computer's OS, hostname and IP address.
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Initialize NetworkTables client and stream server, then connect to the "vision" table.
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Define the camera according to the OS and parameters.
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Define the cascade classifier path. (The classifier we used is trained to detect FRC Power Ports, and can be downloaded from here)
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while True:
- Read the image from the camera.
- Detect the target using the cascade_classifier.detectMultiScale() method.
- If the target is detected, draw a rectangle around it.
- Display the image.
- Send the target's position to the NetworkTables.
- Wait for the next frame.
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Clone the repository.
git clone https://github.com/Scorpions-Robotics/vision-2022.git
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Install the required dependencies.
pip install --upgrade -r requirements.txt
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On Linux you have to install extra dependencies.
cd misc/bash/
chmod +x *
./install_os_dependencies.sh
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Copy
settings.ini.template
and rename it tosettings.ini
. Then edit it to your needs. -
Run the
vision.py
file to start the vision processing.
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Always make sure to run the file from the root directory of the project.
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Always keep the dependencies up to date.
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Always use the latest stable version of this project.
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Instagram: https://instagram.com/scorpions7672
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YouTube: https://www.youtube.com/channel/UCLsK3acedtyaD6dABW39g2Q
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Discord Server: https://discord.gg/MqvbYPecgt
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E-mail: scorpions7672@gmail.com
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Address: Molla Yusuf Mah. Hürriyet Cad. No: 25 Konyaaltı/Antalya, Türkiye
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If you have any suggestions, or found any bugs, please open an issue or create a pull request.
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Don't hesitate to open an issue if you have any questions about the code.
This project is licensed under the Apache-2.0 license. All rights reserved.