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geometric_trans.py

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