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OpenCV is a popular computer vision library, and Qt is a powerful cross-platform GUI toolkit. Combining these two can be beneficial for developing computer vision applications with a user-friendly interface. In this tutorial, we'll walk through the process of installing OpenCV with Qt support using pip and provide a simple code example to demonstrate the integration.
Python: Make sure you have Python installed on your system. You can download it from python.org.
pip: Ensure that you have pip installed. If not, you can install it by following the instructions on the official pip website.
To install OpenCV with Qt support, we will use the following command:
The opencv-contrib-python package includes additional modules, and it's crucial for Qt support. The opencv-python-headless package is a headless version of OpenCV that omits graphical user interface components, which helps reduce the installation size.
After the installation, you can verify that OpenCV is installed correctly by opening a Python terminal and executing the following:
This should print the installed OpenCV version without any errors.
Now, let's install PyQt5, which is a set of Python bindings for Qt:
Create a Python script (e.g., opencv_qt_example.py) and add the following code:
This script creates a simple PyQt5 application that displays a live video stream from your webcam using OpenCV.
You've successfully installed OpenCV with Qt support using pip and created a simple PyQt5 application that integrates with OpenCV. Feel free to customize the code to suit your specific needs and explore the capabilities of both OpenCV and Qt in your computer vision projects.
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