This Python project is a handnail tracking application using TensorFlow and OpenCV. It uses a pre-trained object detection model to detect handnails in real-time from the camera (Webcam) video stream.
- Python 3.x
- TensorFlow
- OpenCV
- NumPy
- Tkinter (for interface use)
- Clone the repository:
$ git clone https://github.com/adinanabf/PowerNail.git
$ cd PowerNail
(You can choose between 2a and 2b)
2a. Install the dependencies:
$ pip install tensorflow opencv-python numpy
2b. Install the requirements into a virtual enviroment
$ python3 -m venv venv
$ source venv/bin/activate
$ python3 -m pip install -r requirements.txt
Run the main.py
script on the root of the directory to start the handnail tracking application:
$ python3 main.py
The application will begin capturing video from the camera and display the video frames with detected handnails in real-time. To exit the application, press the "q" key.
If desired, you can adjust the parameters in the handnail_tracking.py file to suit your needs, such as the pre-trained model, colors used for the ellipses, and opacity.
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The object detection model is based on the TensorFlow Object Detection API.
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Handnail detection is inspired by Victor Dibia's Hand Tracking algorythm.