If no error appears, you are ready to start detecting markers. 2. Download the Standalone C++ Library
Depending on your programming language and project needs, there are three primary ways to "download" and install ArUco. 1. Download for Python (Recommended) how to download aruco
: To ensure it downloaded correctly, open a Python terminal and run: import cv2 from cv2 import aruco print(cv2.__version__) Use code with caution. If no error appears, you are ready to
The easiest way to get ArUco for Python is through the opencv-contrib-python package. This version of OpenCV includes the extra modules (like ArUco) that aren't in the main library. : Use pip to install the full package: pip install opencv-contrib-python Use code with caution. This version of OpenCV includes the extra modules
If you need the ultra-fast, minimal version for a pure C++ project, you can download the source code directly from official repositories. Detection of ArUco Markers - OpenCV Documentation
The library is a crucial tool for developers working on augmented reality (AR), robotics, and camera calibration. While originally a standalone C++ library developed by the University of Córdoba, its most common form today is integrated directly into OpenCV .