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79 lines
3.0 KiB
79 lines
3.0 KiB
import cv2
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import numpy as np
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class edgeDetect:
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def __init__(self, imgPath):
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self.path = imgPath
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def graphicsEnhance(self):
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img_gray = cv2.imread(self.path, 0)
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h, w = img_gray.shape
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gradient = np.zeros((h, w))
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# 计算图像梯度
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img_gray = img_gray.astype('float')
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for i in range(h - 1):
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for j in range(w - 1):
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gx = abs(img_gray[i + 1, j] - img_gray[i, j])
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gy = abs(img_gray[i, j + 1] - img_gray[i, j])
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gradient[i, j] = gx + gy
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# sharp为结果
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sharp = img_gray + gradient
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sharp = np.where(sharp > 255, 255, sharp)
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sharp = np.where(sharp < 0, 0, sharp)
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cv2.imwrite("saved Img/sharp.bmp", sharp)
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def roberts(self):
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img = cv2.imread(self.path)
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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kernelx = np.array([[-1, 0], [0, 1]], dtype=int)
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kernely = np.array([[0, -1], [1, 0]], dtype=int)
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x = cv2.filter2D(img, cv2.CV_16S, kernelx)
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y = cv2.filter2D(img, cv2.CV_16S, kernely)
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absX = cv2.convertScaleAbs(x)
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absY = cv2.convertScaleAbs(y)
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Roberts = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
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cv2.imwrite("saved Img/roberts.bmp", Roberts)
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def sobel(self):
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Sobel = cv2.imread(self.path)
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Sobel = cv2.cvtColor(Sobel, cv2.COLOR_BGR2GRAY)
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x = cv2.Sobel(Sobel, cv2.CV_16S, 1, 0)
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y = cv2.Sobel(Sobel, cv2.CV_16S, 0, 1)
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absX = cv2.convertScaleAbs(x)
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absY = cv2.convertScaleAbs(y)
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Sobel = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
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cv2.imwrite("saved Img/sobel.bmp", Sobel)
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def laplacian(self):
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img = cv2.imread(self.path)
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grayImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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dst = cv2.Laplacian(grayImage, cv2.CV_16S, ksize=3)
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Laplacian = cv2.convertScaleAbs(dst)
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cv2.imwrite("saved Img/laplacian.bmp", Laplacian)
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def LoG(self):
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img = cv2.imread(self.path)
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grayImage = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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img = cv2.copyMakeBorder(grayImage, 2, 2, 2, 2, borderType=cv2.BORDER_REPLICATE)
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img = cv2.GaussianBlur(img, (3, 3), 0, 0)
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m1 = np.array(
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[[0, 0, -1, 0, 0], [0, -1, -2, -1, 0], [-1, -2, 16, -2, -1], [0, -1, -2, -1, 0], [0, 0, -1, 0, 0]],
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dtype=np.int32)
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image1 = np.zeros(img.shape).astype(np.int32)
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h, w, _ = img.shape
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for i in range(2, h - 2):
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for j in range(2, w - 2):
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image1[i, j] = np.sum(m1 * img[i - 2:i + 3, j - 2:j + 3, 1])
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image1 = cv2.convertScaleAbs(image1)
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cv2.imwrite("saved Img/log.bmp", image1)
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def canny(self):
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src = cv2.imread(self.path)
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blur = cv2.GaussianBlur(src, (3, 3), 0)
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grayImage = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)
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gradx = cv2.Sobel(grayImage, cv2.CV_16SC1, 1, 0)
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grady = cv2.Sobel(grayImage, cv2.CV_16SC1, 0, 1)
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edge_output = cv2.Canny(gradx, grady, 50, 150)
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cv2.imwrite("saved Img/canny.bmp", edge_output)
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