How To Install OpenCV Using Pip


By squashlabs, Last Updated: October 8, 2023

How To Install OpenCV Using Pip


OpenCV is a popular open-source computer vision library that provides a wide range of functions and algorithms for image and video processing. It is widely used in various fields such as robotics, augmented reality, and machine learning. Installing OpenCV using pip is a convenient method, as it allows you to easily manage and update the library.

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Reasons for Installing OpenCV Using pip

There are several reasons why you might want to install OpenCV using pip:

1. Simplicity: pip is the default package manager for Python and is widely supported across different platforms. Using pip to install OpenCV ensures a straightforward installation process.

2. Package Management: pip enables you to easily manage and update OpenCV and its dependencies. You can use pip to install specific versions of OpenCV or upgrade to the latest release with just a few commands.

3. Compatibility: Installing OpenCV using pip ensures compatibility with other Python packages that you may be using in your project. It allows you to easily integrate OpenCV with other libraries and frameworks.

Step-by-Step Instructions to Install OpenCV Using pip

Step 1: Check Python Version

Before installing OpenCV, it is important to check that you have Python installed on your system. Open a terminal or command prompt and run the following command:

python --version

Ensure that the Python version displayed is compatible with the version of OpenCV you intend to install. OpenCV supports Python 2.7, as well as Python 3.4 and above.

Step 2: Install pip

If you don’t already have pip installed, you can install it by following the instructions on the official Python website:

Step 3: Install OpenCV

Once pip is installed, you can use it to install OpenCV. Open a terminal or command prompt and run the following command:

pip install opencv-python

This command will install the latest stable version of OpenCV along with its dependencies.

Step 4: Verify the Installation

To verify that OpenCV has been successfully installed, you can run a simple test script. Create a new Python file called and add the following code:

import cv2

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

Save the file and run it using the following command:


If OpenCV is installed correctly, you should see the version number printed in the console.

Alternative Methods

While installing OpenCV using pip is the recommended method, there are alternative methods available:

1. Building from Source: If you require a specific version of OpenCV or need to customize the installation, you can build OpenCV from source. This method provides more flexibility but may require additional dependencies and compilation steps. Instructions for building OpenCV from source can be found in the official OpenCV documentation.

2. Using Conda: If you are using the Anaconda distribution, you can install OpenCV using the conda package manager. Conda provides a convenient environment for managing packages and dependencies. To install OpenCV using conda, you can run the following command:

conda install opencv

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Best Practices

When installing OpenCV using pip, it is recommended to follow these best practices:

1. Virtual Environments: Create a virtual environment for your Python project to isolate the OpenCV installation from other projects. This allows you to manage package dependencies more effectively and avoids conflicts between different versions of OpenCV.

2. Version Pinning: If you require a specific version of OpenCV, you can specify it in your project’s requirements.txt file. This ensures that the same version of OpenCV is installed across different environments and avoids compatibility issues.

3. Regular Updates: Keep your OpenCV installation up to date by regularly checking for updates and upgrading to the latest stable release. This ensures that you have access to the latest features, bug fixes, and security patches.

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