Installing OpenCV on MacBook Pro with M1 Chip

If you’re a developer passionate about computer vision and machine learning, OpenCV is an indispensable library that can help you unlock new possibilities.

In this step-by-step guide, we’ll walk you through the process of installing OpenCV on your MacBook Pro equipped with the powerful M1 chip.


Before we embark on our journey, ensure you have Homebrew installed on your system.
If it’s not already installed, you can easily get it with this command:

brew install cmake

Now, let’s dive into the exciting world of OpenCV installation.

A Visionary Installation Process

  1. Create a Dedicated Directory: Start by creating a dedicated directory for OpenCV and navigate into it. This will keep your workspace organized:
mkdir Open_CV && cd Open_CV
  1. Clone the OpenCV Repository: The next step is to clone the OpenCV repository from GitHub. This will give you access to the latest source code:
git clone
  1. Build Configuration: Create a ‘build’ directory within your OpenCV workspace and navigate into it. Here’s where you configure your build using CMake. Below are some options to consider (customize them to fit your specific needs):
arch -arm64 cmake ../opencv/ \
  1. Compile with Power: Utilize the powerful capabilities of your M1 chip by compiling OpenCV with multiple cores for faster compilation. Adjust the -j flag according to the number of CPU cores you have:
arch -arm64 sudo make -j 4
  1. Installation: The final step involves installing OpenCV on your system:
arch -arm64 sudo make install

A Glimpse of Success

To ensure that OpenCV has been successfully installed, let’s perform a quick verification.
Create a simple Python script to check the installed OpenCV version:

import cv2

print("OpenCV Version:", cv2.__version__)

Save this script as and execute it:


If all goes well, you should see the installed OpenCV version proudly displayed in your console.

Conclusion: A Vision Realized

Congratulations! You’ve successfully installed OpenCV on your MacBook Pro with an M1 chip.
This remarkable computer vision library is now at your disposal, ready to fuel your creativity and innovation in image and video processing projects.

As you embark on this journey of exploration, remember that OpenCV is your trusted companion in the world of computer vision. From image recognition to augmented reality, the possibilities are endless.

Start your adventure now and bring your vision to life!

Happy coding!

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  • gerardo

    it works!, I tried to test a python script but I didn’t compile, I must to install this command:
    pip install opencv-python
    and now works perfectly, thank you.

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