From the course: Programming Foundations: Artificial Intelligence

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Dive into computer vision

Dive into computer vision

From the course: Programming Foundations: Artificial Intelligence

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Dive into computer vision

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- [Instructor] Computer vision enables computers to interpret and understand visual information from the world, such as images and videos. In this video, we will use OpenCV, Open Source Computer Vision Library, to implement a basic computer vision project that processes and analyzes images. We'll detect edges in an image using the Canny Edge Detection algorithm. I've navigated to the Jupyter Notebook. You can find the notebook in the GitHub repo. First, I install OpenCV because it's not present on my machine. Then I import the necessary libraries. We import cv2. OpenCV contains more than 2,500 optimized algorithms that can be used for various tasks in computer vision and image processing. We also import matplotlib for displaying images. Make sure you install it before attempting to import it. Scroll down in cell 12. We load the image of a palm tree from the specified path using cv2.imread You can find the palm tree in the GitHub repo. Scroll down to cell 13. Here, we convert the image…

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