15 Mar Edge Detection with OpenCV
Create a sketch-like effect by detecting edges in the image. Detect edges using the Canny edge detector i.e. the Canny() function. Let us see the example of detecting edges with OpenCV:
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# Read and display an image with OpenCV. Detect the edges. import cv2 # Load an image image = cv2.imread(r'C:\Users\hp\Downloads\Astronaut.png') # Detect edges using the Canny edge detector edges = cv2.Canny(image, 100, 200) # Display the result cv2.imshow("Edge Detection Filter", edges) # Wait for a key press and close the window cv2.waitKey(0) cv2.destroyAllWindows() |
The following is the output:
Explanation:
This Python script uses the OpenCV library to load an image, detect its edges using the Canny edge detection algorithm, and display the result:
- It begins by importing OpenCV and loading the specified image into the variable
imageusing thecv2.imread()function. - The Canny edge detector is then applied to the image using
cv2.Canny(), which identifies edges by detecting areas of rapid intensity change. This function takes three arguments: the input image, the lower threshold (100), and the upper threshold (200). - The resulting edge-detected image is stored in the variable
edges. - The script then displays the processed image in a window titled “Edge Detection Filter” using
cv2.imshow(). - To keep the display window open, it waits indefinitely for a key press with
cv2.waitKey(0)and closes all OpenCV windows usingcv2.destroyAllWindows(). - This allows users to visualize the edges of the image clearly and interactively.
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