# 定义旋转rotate函数 def rotate(image, angle, center=None, scale=1.0): # 获取图像尺寸 (h, w) = image.shape[:2] # 若未指定旋转中心,则将图像中心设为旋转中心 if center is None: center = (w / 2, h / 2) # 执行旋转 M = cv2.getRotationMatrix2D(center
//Width and height of magMat should be even, so that they can be divided by 2 //-2 is 11111110 in binary system, operator & make sure width and height are always even magMat = magMat(Rect(0, 0, magMat.cols & -2, magMat.rows & -2)); //Rearrange the quadrants of Fourier i...
创建python脚本rotation.py,并输入以下内容: # 导入库importnumpyasnpimportargparseimportcv2# 定义旋转rotate函数defrotate(image,angle,center=None,scale=1.0):# 获取图像尺寸(h,w)=image.shape[:2]# 若未指定旋转中心,则将图像中心设为旋转中心ifcenterisNone:center=(w/2,h/2)# 执行旋转M=cv2.getRotatio...
angle = theta# 仿射变换,对图片旋转angle角度h, w = img.shape center = (w//2, h//2) M = cv2.getRotationMatrix2D(center, angle,1.0) rotated = cv2.warpAffine(img, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)# 保存旋转后的图片cv2.imwrite('F://CHN_Char/aft...
angle = 45 # 旋转角度 scale = 1.0 # 缩放比例 M = cv2.getRotationMatrix2D(center, angle, scale) # 应用仿射变换 dst = cv2.warpAffine(img, M, (cols, rows)) # 保存结果 # cv2.imwrite('output.jpg', dst) # 显示结果 cv2.imshow('Rotated Image', dst) ...
// create the rotation matrix using the image centerMat rotation_matix = getRotationMatrix2D(center, angle=45, 1.0); 现在,使用warpAffine()函数将计算的旋转矩阵应用于图像。它需要三个输入: 源图像 旋转矩阵 输出图像的大小 Python # Rotate the image using cv2.warpAffinerotated_image = cv2.warpAffine...
import cv2 def rotate_image(mat, angle): """ Rotates an image (angle in degrees) and expands image to avoid cropping """ height, width = mat.shape[:2] # image shape has 3 dimensions image_center = (width/2, height/2) # getRotationMatrix2D needs coordinates in reverse order (width...
. @param img Image. . @param center Center of the ellipse. . @param axes Half of the size of the ellipse main axes. . @param angle Ellipse rotation angle in degrees. . @param startAngle Starting angle of the elliptic arc in degrees. ...
returnangle;}intmain(){Mat img=imread("./clip.png");if(img.empty()){cout<<"Read image error, please check again!"<<endl;return1;}imshow("src",img);Mat gray;cvtColor(img,gray,CV_BGR2GRAY);threshold(gray,gray,85,255,CV_THRESH_BINARY_INV);//二值化imshow("threshold",gray);vector...
frame= imutils.rotate(frame, angle=180) 请注意,这里使用的颜色掩膜的边界值是我们在上一步得到的。 06. 测试通用 IO 现在我们已经搞定OpenCV的基础了,是时候给树莓派装个LED来试一下通用IO了。 请按照上图的电路做:LED的负极接到GPIO 21口,正极接一个220Ω的电阻再连接GND。