Opencv mac os build make

Install OpenCV 3 on MacOS

In this post, we will provide step by step instructions for installing OpenCV 3.3.0 (C++ and Python) on MacOS and OSX.

Step 1: Install XCode

Install XCode from App Store.

If XCode available on App Store is not compatible with your OS:

1. Find XCode version compatible to your OS from this table https://en.wikipedia.org/w/index.php?title=Xcode#Version_comparison_table
2. Go to this webpage https://developer.apple.com/download/more/
   • Login if you have apple developer account else create your account and login.
   • Search for xcode and download the version compatible to your OS.
3. Install XCode.
4. After installation open XCode, and accept xcode-build license when it asks.

Step 2: Install Homebrew

Launch a terminal from Launchpad. From this step onward, all commands will be run in the terminal.

Step 3: Install Python 2 and Python 3

Python version (2.6 or 2.7, 3.5 or 3.6) installed on your machine is required to determine path of Python’s site-packages. It will be used later.

NOTE : Recently Homebrew made some changes in Python formula. Earlier homebrew used to install python2 as /usr/local/bin/python. Now it follows these rules:

1. Install python2 at /usr/local/bin/python2
2. Install python3 at /usr/local/bin/python3
3. python command will point to /usr/bin/python. This is the python distribution which comes with your OS and not installed by Homebrew.

We want to use Python installed by Homebrew because it makes installing/managing packages easier. To run python scripts you should run command python2 and python3 for Python 2 & 3 respectively. If you find this annoying and want to use command python to run python2, add following line to

This step is recommended not just for this course but in general to keep the python installation clean.

Step 4: Install Python libraries in a Virtual Environment

We will use Virtual Environment to install Python libraries. It is generally a good practice in order to separate your project environment and global environment.

Step 5: Install OpenCV

Step 5.1 : Compile & Install OpenCV

Note: Homebrew recently moved many popular formulae to homebrew-core.
Earlier you can install OpenCV 2 using formula name opencv and OpenCV 3 using formula name opencv3.
They have now renamed opencv3 to opencv and opencv to [email protected]
Various options such as –with-qt, –with-tbb etc are also removed in the updated formula and CUDA support is also dropped.
You can check these github issues 15853, 6126, 16640, 5996
to read more about it.

Homebrew has also made it compulsory to compile and install Python bindings for both Python 2 and Python 3. So if you don’t have Python 3 installed, Homebrew will install it while installing opencv.

Step 5.2 : Add OpenCV’s site-packages path to global site-packages

When brew is done compiling and installing OpenCV3, we will update path of site-packages directory which contains cv2.so file to Homebrew Python’s site-packages directory. Depending upon the Python version you have (2.6/2.7 or 3.5/3.6) these paths would be different.

Step 6: Make OpenCV3 Python symlink in our virtual environment

Path to OpenCV’s Python library will be different depending upon which Python version you have. Double check the exact path and filename on your machine. Use this command to find out the path on your machine.

Step 7: Test OpenCV3

Now you can exit from Python virtual environment.

Now whenever you are going to run Python scripts which use OpenCV you have to activate the virtual environment we created using workon command.

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Building and Installing OpenCV 4.5.0 on an M1 Mac

This post shows how to build and install OpenCV 4.5.0 on a MacBook Pro that comes with an M1 chip.

Jan 1, 2021 • Sayak Paul • 4 min read

This post shows how to build and install OpenCV 4.5.0 on a MacBook Pro that comes with an M1 chip. Yes, you guessed it right — as of January 01, 2021, there’s no pre-compiled OpenCV binary compatible with this MacBook Pro variant. So, open up a terminal and get started!

Here’s a brief summary of the configuration of my MacBook —

Note: The following steps should run well on an M1 MacBook Air too.

Install Xcode and Homebrew

We start by executing sudo xcodebuild -license from a terminal.

When you execute the above command, you would need to accept the Xcode license. Then, in order to make use of Apple command line tools, we need to install it — sudo xcode-select —install .

Homebrew manages packages on a Mac. In order to install it execute the following — /usr/bin/ruby -e «%(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)» .

You would want to add the command brew after the installation is complete. To do so, execute the following — nano

Then insert export PATH=$PATH:/opt/homebrew/bin into it and press Ctrl + X from your keyboard. Then execute source

/.zshrc from the terminal.

Note that the exact path to Homebrew might be different for your system, so please double check that.

Next up, we install a few system-level utilities required by OpenCV on a Mac.

Install conda

My favorite Python virtual environment manager is virtualenv. Unfortunately, it does not play out that well with the new M1 chip. This is mostly because the pip-installable packages often break during their installations on the chip. This is why conda, specifically its miniforge distribution is the recommended package manager for a Mac shipped with M1. You can install it from here. This installs Python 3.8.

After the installation is complete, please create a new Python virtual environment by executing conda create —name . Then activate it by running conda activate .

Running conda install -y python==3.8.6 will install a few common Python packages for you. I highly recommend running this.

Install NumPy

NumPy is needed by OpenCV. So, we need to install it before we build and install OpenCV. Apple provides a numpy wheel that is compatible with the M1 chip. Follow the steps below to install it —

Note: Be sure to activate your conda environment before doing the pip-install.

Compile OpenCV

First, let’s download the OpenCV and OpenCV extended module files and prepare them for compilation.

Now, we are all set to fire the cmake command that would build OpenCV for us. Let’s review it briefly —

As per this issue comment, DCMAKE_SYSTEM_PROCESSOR , DCMAKE_OSX_ARCHITECTURES , DWITH_OPENJPEG , and DWITH_IPP are needed to be set during the compilation step. Also, please pay attention to the following arguments — OPENCV_EXTRA_MODULES_PATH and PYTHON3_EXECUTABLE . For these two arguments, you would want to first determine the paths and then supply them accordingly.

Now, before you run the above cmake command, activate the conda environment you created in an earlier step ( conda activate ) if you haven’t already. The compilation took

3 minutes for me and it should produce outputs like so —

Next, we launch the make command — make -j8 . With all the eight cores ( j8 stands for eight cores here) chugging along, this step took

8 minutes for me. You can adjust the j option with respect to the hardware available. After it’s done you should get an output like so —

The final step here is to execute — sudo make install . It should take just a few seconds to complete execution. Upon successful completion, you should get an output like so —

Sym-link OpenCV 4 on macOS to virtual environment site-packages

To do this, we first need to locate the .so file generated during the compilation step. We can do this with the mdfind command —

Please note that I obfuscated some parts of the outputs for privacy reasons. In the above output, we can see the absolute locations for the .so files that were generated. Now, we need to execute the following to sym-link one of the .so files in our current Python virtual environment —

Please double-check the paths before executing the commands.

You can test the installation by executing the following —

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Building and Installing OpenCV on M1 Macbook

Prabhat Kumar Sahu

May 27 · 5 min read

In this blog post, we are going to build and install OpenCV on anM1 Mac.

Last year in November 2020 apple releases their first ARM64-based M1 chip. It got a lot of attention from everyone.

Being a tech enthusiast and a programmer, I was amazed to see the performance of the new apple M1 chip. The benchmarks were really good.

Recently only some months back, I bought myself an M1 Macbook Pro with 8Gigs of RAM and 512GB of SSD.

Let’s get started.

Here are the things that we are going to do.

• Step 1: Homebrew and Xcode Command Line Tools Installation
• Step2: Install Miniforge
• Step3: Create a virtual environment with python3.8
• Step4: Install necessary dependencies
• Step5: Compile and Build OpenCV
• Step6: Test OpenCV

Step1: Homebrew and XCode CLI Installation

If Home b rew is not already installed in your system you can install it by running the following in your terminal.

After it gets installed, install wget and CMake.

I have already installed Xcode Command Line Tools on my mac. If it’s not already installed in your system, you can install it by running the following command below in your terminal.

Step2: Install Miniforge

Install miniforge for arm64 (Apple Silicon) from miniforge GitHub.

Miniforge enables installing python packages natively compiled for Apple Silicon.

After the installation of miniforge, by default, it gives us one base environment. You can turn off the default base env by running

Step3: Create a virtual environment

Let’s create a virtual environment named cv2 with python3.8 installed.

And activate it by running

Step4: Installing Some Dependencies

As we are going to install OpenCV natively we have to install the compatible version of Numpy which Apple provides for M1.

Run the following commands below on a terminal to install Numpy and some other dependencies.

Step5: Compile and Build OpenCV

We have to download OpenCV and OpenCV Contrib first.

I have created one folder named test_opencv where I will be downloading files and build there.

Let’s Set up the OpenCV build with CMake:

Make sure to put your own PATH on OPENCV_EXTRA_MODULES

Also, make sure to activate your conda environment before running make.

You have to put your Python3 executable path also. You can get it by running

For eg: My path is

You have to change and put your own path there.

Now you can run

You will see the screen below after Cmake. The compilation doesn’t take that much time.

Now we have the run the make command.

Here j8 stands for 8 cores. You can do either make or you can adjust the j option . So let’s run

You will get an output like the below. It took around 10 minutes for me.

Then the last step is to run

You will get the above after sudo make install.

Sym-link OpenCV 4 on macOS to virtual environment site-packages

We need to first locate the .so file, which has been generated during the compilation of OpenCV.

Now, we need to execute the following to sym-link one of the .so files in our current Python virtual environment.

You can see this from the screenshot. There’s one so file that has been generated inside the build folder. The path to the .so file in my system is

Also, Please double-check the paths before executing the commands.

Open up another terminal and go to your python environment site-packages directory. In my case it’s

And execute the sym-link

This I ran on my second terminal.

And that’s it. Now we are good to go.

Open a separate terminal if you want and activate your virtual environment

And just run the below

Step6: Test OpenCV by running a program

Create a new file named main.py and paste the code below. Put a dummy photo for test purposes in the third line. The code just converts the image to a black-white image.

And run it python3 main.py. Here’s the output

Additional Step

If you want to uninstall OpenCV, you can go inside the build folder and run

It will remove OpenCV 4.5.0 from your system. Also, you can delete your conda environment. First, deactivate if it’s activated

It will remove completely.

We were able to build and install OpenCV 4.5.0 successfully in our M1 Mac and we are able to run some code also.

If you have any questions, recommendations, or critiques, I can be reached via Twitter or via my mail. Feel free to reach out to me.

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