# let's rotate an image 45 degrees clockwise using OpenCV by firstcomputing the image center, then constructing the rotation matrix,and then finally applying the affine warp#让我们使用OpenCV顺时针旋转图像45度,首先计算图像中心,然后构造旋转矩阵,最后应用仿射扭曲来达到旋转效果center=(w//2,h//2)M=...
cv2.imshow("Original", image) # 将原图旋转不同角度 rotated = rotate(image, 45) cv2.imshow("Rotated by 45 Degrees", rotated) rotated = rotate(image, -45) cv2.imshow("Rotated by -45 Degrees", rotated) rotated = rotate(image, 90) cv2.imshow("Rotated by 90 Degrees", rotated) r...
rotated = cv2.warpAffine(image, M, (w, h)) cv2.imshow("Rotated by 45 Degrees", rotated) cv2.waitKey(0) # 锐化 def image_sharpen(image): kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]], np.float32) #定义一个核 image_sharpen = cv2.filter2D(image, -1...
# use the imutils function to rotate an image 30 degrees rotated = imutils.rotate(image, -30) cv2.imshow("Rotated by 30 Degrees", rotated) cv2.waitKey(0) 调用imutils.rotate函数,通过将图像和旋转角度作为参数传递,将图像沿所需方向旋转。 输出: 就像在前面的图像中一样,旋转会切断图像的某些部分...
rotated = imutils.rotate(image, 180) #18 cv2.imshow("Rotated by 180 Degrees", rotated) #19 cv2.waitKey(0) #20 #1-9: 与前几节一样的操作,进行导包,然后显示原始图片,但是需要注意的是在第三行 import imutils,还记得它是什么吗?我们在上一节还详细介绍过啊。忘记了,可以返回上一节看看。
rotate_angle = math.degrees(math.atan(t)) ifrotate_angle >45: rotate_angle = -90+ rotate_angle elifrotate_angle < -45: rotate_angle =90+ rotate_angle # 图像根据角度进行校正 rotate_img = ndimage.rotate(img, rotate_angle) # 在图中画出线 ...
cv2.imshow("Rotated by -90 Degrees",rotated) rotated = imutils.rotate(image,60,None,0.5) cv2.imshow("Rotated by imutils",rotated) cv2.waitKey(0) 封装rotate方法 工具类imutils.py def rotate(image, angle ,center= None,scale =1.0): ...
rotated=rotate(image,45)cv2.imshow("Rotated by 45 Degrees",rotated)rotated=rotate(image,-45)cv2.imshow("Rotated by -45 Degrees",rotated)rotated=rotate(image,90)cv2.imshow("Rotated by 90 Degrees",rotated)rotated=rotate(image,-90)cv2.imshow("Rotated by -90 Degrees",rotated)rotated=...
cv2.imshow("Rotated by 45 Degrees",rotated) cv2.waitKey(0)#旋转-45度。缩放1.25M = cv2.getRotationMatrix2D(center,-45,1.25)#旋转缩放矩阵:(旋转中心。旋转角度,缩放因子)rotated = cv2.warpAffine(image,M,(w,h)) cv2.imshow("Rotated by -90 Degrees",rotated) ...