Dart Master
Description
This Project was part of the VR/AR course at my university TU Darmstadt. The aim of the Project was to crate an
automatic dart scorer application, where two players can play a game of dart without focusing on the point counting.
The application uses OpenCV for the computer vision part and Pyside2 for the GUI.
We use a calibrated webcam to capture a video stream and process it with OpenCV to extract the darts on the board and
keep track of the players.
Demo Video
How it works
The complete detection pipline looks something like this:
- First detect the aruco markers
- detect the dart board with a circle detector
- fit a polar coordinate system to the dart board
- take the reference image
- some filters to remove noise and improve the detection
- calculate the difference image between the reference image and the current image
- contour detection on the difference image
- contour > minimum area filter
- fit triangle to the contour
- find the tip of the dart by using the corner opposite of the shortest side
- correct the tip position by moving it to the center of the triangle relative to its size
- getting the position of the tip relative to the polar coordinate system
- Evaluation of the score with DartScorer()
The overall pipeline is summarized in this flowchart:
Setup
Hardware
You will need:
- a webcam
- something to mount the webcam
- a computer
- a dartboard
- the 4 aruco markers that can be found in Resources/Doku/
Place the Markers around the dartboard like in the image below and make sure they are visible.
Place the webcam in front of the dartboard approximately 1 meter away and slightly to the right,
so it doesn’t get in the way with throwing the darts.
Important: You need good lighting to get good results. Only Lighting from directly above the dartboard is bad.
Optimal would be a ring light with a diffusor like this:
We had some problems with shaking of the board wich induced noise in the detection.
We solved this by 3D printed mounts for the board:
Software
Just clone the repository and run the following command:
pip install -r requirements.txt
First you need to calibrate the camera. This can be done with the Calibration Script.
Then you can start main_with_gui.py.
The GUI looks like this:
Short Instructions
- First select your starting Points (501, 301 or 101) for your dart game.
- Then set the default image with the button “Set Default”.
- After that you can start the detection with “Start”
- If the darts are detected badly you can adjust the threshold with the slider.
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