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import cv2
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import numpy as np
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# 扩展
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def extend(img):
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l, w, h = img.shape
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# 放大图像至原来的两倍，使用双线性插值法
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img=cv2.resize(img,(0,0),fx=2,fy=2,interpolation=cv2.INTER_LINEAR)
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cv2.imwrite("image/result.jpg", img)
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#平移
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def move():
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img=cv2.imread('test.png')
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height, width, channel = img.shape
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# 构建移动矩阵,x轴左移 10 个像素，y轴下移 30 个
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M=np.float32([[1,0,30],[0,1,60]])
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img = cv2.warpAffine(img, M, (width, height))
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cv2.imwrite("image/result.jpg", img)
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#旋转
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def rotate():
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img=cv2.imread('test.png')
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# 构建矩阵，旋转中心坐标为处理后图片长宽的一半，旋转角度为45度，缩放因子为1
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height, width, channel = img.shape
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rows,cols,depth=img.shape
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M=cv2.getRotationMatrix2D((cols/2,rows/2),45,1)
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img = cv2.warpAffine(img, M, (width, height))
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cv2.imwrite('image/result.jpg', img)
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# 翻转
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def Flip(src):
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########Begin########
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#图像放缩
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src=cv2.resize(src,(256,256))
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#水平镜像
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horizontal=cv2.flip(src,1)
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#垂直镜像
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vertical=cv2.flip(src,0)
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#对角镜像 ，并保存
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cross=cv2.flip(src,-1)
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cv2.imwrite("image/result.jpg", cross)
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# 仿射变换
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def affine_trans(src):
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src = cv2.resize(src, (256, 256))
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# 获取图像shape
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rows, cols = src.shape[: 2]
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post1=np.float32([[50,50],[200,50],[50,200]])
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post2=np.float32([[10,100],[200,50],[100,250]])
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M=cv2.getAffineTransform(post1,post2)
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result = cv2.warpAffine(src,M,(rows,cols))
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cv2.imwrite("image/try.jpg", result) |
