OpenCV stands for “Open Source Computer Vision Library”. It is an open-source computer vision and machine learning software library. Today, we will dive into how to display an image using OpenCV in Python.
Python is an extensively used high-level programming language for general-purpose programming, favored for its easy readability with excellent design principles.
Step 1: Installation
Firstly, ensure that both Python and OpenCV are installed on your local system. You can download the latest version of Python from their official website, and OpenCV from their official website.
Step 2: Importing Required Libraries
After successful installation, you need to import the necessary library:
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import cv2 |
Step 3: Reading the Image
In this step, we will read the image using the method imread(). The image should be in the same directory that you’re script is running from, otherwise, you should provide a full path to the image.
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img = cv2.imread('image.jpg') |
Step 4: Displaying the Image
To display the image, we can use the method imshow(). It takes two arguments: the first is a window name which is a string. the second argument is our image. You can create as many windows as you wish but with different window names.
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cv2.imshow('image', img) |
Step 5: Waiting for Keyboard Events
The next line is a keyboard binding function, which takes time in milliseconds as an argument. The function waits for specified milliseconds for any keyboard event. If the event is triggered, the program continues.
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cv2.waitKey(0) |
Step 6: Destroy All Windows
The next step is to close windows and de-allocate memory usage with the method destroyAllWindows().
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cv2.destroyAllWindows() |
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# Full Code import cv2 img = cv2.imread('image.jpg') cv2.imshow('image', img) cv2.waitKey(0) cv2.destroyAllWindows() |
Conclusion
Displaying an image in Python using OpenCV is a straightforward process and incredibly useful, especially in image analysis or machine learning projects. By following these steps, you are able to easily import, load, and view an image. It’s the first basic step in working with image data in Python using OpenCV.