This project uses computer vision to detect the state of a Rubik's cube and then provides a solution using the Kociemba algorithm (two-phase solver). It leverages ArUco markers placed on the center pieces of each face to identify the faces and their orientation.
- Camera Calibration: Calibrates your webcam to minimize distortion and improve accuracy.
- Aruco Marker Detection: Detects ArUco markers on the Rubik's Cube faces.
- Color Detection: Determines the color of each cubie on the detected face using a calibration process.
- Cube State String Generation: Creates the cube definition string needed by the Kociemba solver.
- Solution Visualization: Displays an interactive 3D Rubik's cube and animates the solution steps.
- Python 3.7+
- Libraries:
numpy==2.2.1opencv-contrib-python==4.10.0.84kociemba==1.2.1ursina(for visualization)