def skeletonize(image, *, method=None): """Compute the skeleton of a binary image. Thinning is used to reduce each connected component in a binary image to a single-pixel wide skeleton. Parameters --- image : ndarray, 2D or 3D An image containing the objects to be skeletonized. Zeros r...
02使用skimage实现骨架提取 有两个相关的函数实现二值图像的骨架提取,一个是基于距离变换实现的medial_axis方法;另外一个是基于thin的skeletonize骨架提取方法。两个方法的代码实现分别如下: 1def skeleton_demo(image): 2 gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) 3 ret, binary = cv.threshold(gray, 0,...
实例代码: image = cv2.imread("jpg.png")#实施骨架算法image1=morphology.skeletonize(image)#显示结果plt.imshow(image1) plt.axis('off') plt.show() 7)边缘检测 实例代码: #边缘检测image2= cv2.Canny(image,80,255) cv2.imshow("image2",image2) cv2.waitKey(0) 图3.7边缘检测的图片 8)图片反色 ...
cv2.threshold(img6,80,1,0,img6) img7=morphology.skeletonize(img6) plt.imshow(img7,cmap=plt.cm.gray) plt.axis('off') plt.show() #图像反色h1,w1 =img7.shape img8=img7.copy()foriinrange(h1):forjinrange(w1): img8[i,j]= 1-img8[i,j] plt.imshow(img8,cmap=plt.cm.gray) plt...
骨架提取是将二值图像减少到1像素宽的表示。这对于特征提取和(或)表示对象的拓扑结构非常有用。# pip install scikit-image from skimage.morphology import skeletonize from skimage import data import matplotlib.pyplot as plt from skimage.util import in ...
% skeletonizeimSkele=bwmorph(imBW,'skel',inf);figure;imshow(imSkele)title('Skeleton image')% ...
使得读者能够对“投影技术”加速认识和理解，从而在解决具体问题的时候多一个有效方法。我第一次集中遇到...
skeletonize: a Delphi/Lazarus demo program that reduces an image to its more basic contours ("skeleton") camshiftdemo: a Delphi/Lazarus demo program, adapted from a classical Opencv example; the program tracks movements of a selected area in real time on webcam, for example the face of perso...
// skeletonize the image Mat gray = imread("pyimagesearch_logo.jpg", 0); Mat skeleton = imutils::skeletonize(gray, cv::Size(3, 3)); imshow("Skeleton", skeleton); Automatic Canny Edge Detection The Canny edge detector requires two parameters when performing hysteresis. However, tuning these...
However, the media pipe library first skeletonizes that image. Utilizing a variety of deep learning models, the input obtained from the yoga postures is improved to improve the asana. The algorithms like VGG16 (Visual Geometric Group), VGG19, Convo2d, CNN.ANURADHA T....