# 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...
(h,w) = image.shape[:2] center = (w / 2,h / 2) #旋转45度,缩放0.75 M = cv2.getRotationMatrix2D(center,45,0.75)#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 45 Degrees",rotated) cv2.waitKey(0) #旋转-45度,缩放...
# 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...
roi = image[60:160, 320:420] cv2.imshow("ROI", roi) cv2.waitKey(0) 数组切片的格式为:image[startY:endY, startX:endX],注意前闭后开 6.调整图像大小 调整图像大小很重要,原因有很多。首先,我们可能需要调整大图像的大小以适合屏幕。在较小的图像上,图像处理也更快,因为要处理的像素更少。在深度...
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): ...
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) ...
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。
cv::warpAffine(image, dest, r, cv::Size(len, len));break;//image size will change} } opencv3: voidcv::rotate(InputArray src, OutputArray dst,introtateCode ) Rotates a 2D array in multiples of 90 degrees. The function rotate rotates the array in one of three different ways: Rotate ...
imshow("original image",img) (h, w) = img.shape[:2] (cX, cY) = (w / 2, h / 2) # rotate our image by 45 degrees M = cv2.getRotationMatrix2D((cX, cY), -1.2, 1.0) rotated = cv2.warpAffine(img, M, (w, h)) #cv2.imshow("Rotated by 45 Degrees", rotated) cropedImg...