CPDA角点检测算法的python实现
CSS角点检测算法的python实现
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关注 使用Python实现CPDA算法的代码
import cv2 import numpy as np def cpda(image): # Convert the image to grayscale gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Calculate the gradient in x and y direction using Sobel filter sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0) sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1) # Calculate the magnitude of the gradient mag = np.sqrt(sobelx**2 + sobely**2) # Threshold the magnitude image to obtain binary image threshold = np.max(mag) * 0.1 binary = np.zeros_like(mag) binary[mag > threshold] = 1 # Apply morphological operations to remove noise kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5,5)) closed = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel) opened = cv2.morphologyEx(closed, cv2.MORPH_OPEN, kernel) # Find the corners using the Harris corner detector corners = cv2.cornerHarris(opened, blockSize=2, ksize=3, k=0.04) corners = cv2.dilate(corners, None) # Threshold the corner image to obtain binary image threshold = np.max(corners) * 0.1 binary = np.zeros_like(corners) binary[corners > threshold] = 1 # Return the corner locations as a list of (x,y) tuples return list(zip(*np.nonzero(binary)[::-1])) # Load an image image = cv2.imread("image.jpg") # Detect the corners using CPDA algorithm corners = cpda(image) # Draw the corners on the image for x, y in corners: cv2.circle(image, (x,y), 5, (0,0,255), -1) # Display the image cv2.imshow("Corners", image) cv2.waitKey(0) cv2.destroyAllWindows() ```python
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