{"id":1088975,"date":"2025-01-08T13:49:16","date_gmt":"2025-01-08T05:49:16","guid":{"rendered":""},"modified":"2025-01-08T13:49:18","modified_gmt":"2025-01-08T05:49:18","slug":"%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8python%e4%b8%ad%e7%9a%84cv2-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1088975.html","title":{"rendered":"\u5982\u4f55\u4f7f\u7528python\u4e2d\u7684cv2"},"content":{"rendered":"

\"\u5982\u4f55\u4f7f\u7528python\u4e2d\u7684cv2\"<\/p>\n

\u5982\u4f55\u4f7f\u7528python\u4e2d\u7684cv2<\/strong><\/p>\n<\/p>\n

\u5728Python\u4e2d\u4f7f\u7528cv2\u5e93\uff08\u5373OpenCV\uff09\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u65f6\uff0c\u5173\u952e\u6b65\u9aa4\u5305\u62ec\uff1a\u5b89\u88c5OpenCV\u3001\u5bfc\u5165\u5e93\u3001\u8bfb\u53d6\u56fe\u50cf\u3001\u663e\u793a\u56fe\u50cf\u3001\u5904\u7406\u56fe\u50cf\u3001\u4fdd\u5b58\u56fe\u50cf<\/strong>\u3002\u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u5730\u5904\u7406\u56fe\u50cf\u3001\u8fdb\u884c\u8fb9\u7f18\u68c0\u6d4b\u3001\u8f6c\u6362\u989c\u8272\u7a7a\u95f4\u7b49\u3002\u4ee5\u4e0b\u662f\u5bf9\u5176\u4e2d\u51e0\u9879\u7684\u8be6\u7ec6\u63cf\u8ff0\u3002<\/p>\n<\/p>\n

\u5b89\u88c5OpenCV<\/strong><\/p>\n

\u9996\u5148\uff0c\u9700\u8981\u5728\u7cfb\u7edf\u4e2d\u5b89\u88c5OpenCV\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u6765\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5bfc\u5165cv2\u5e93\u8fdb\u884c\u4f7f\u7528\u3002<\/p>\n<\/p>\n
\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u50cf<\/strong><\/p>\n
\u8bfb\u53d6\u56fe\u50cf\u662f\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u7684\u7b2c\u4e00\u6b65\u3002\u53ef\u4ee5\u4f7f\u7528cv2.imread()\u51fd\u6570\u8bfb\u53d6\u56fe\u50cf\uff0c\u5e76\u4f7f\u7528cv2.imshow()\u51fd\u6570\u663e\u793a\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('image.jpg')<\/p>\n
\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n
cv2.imshow('Image', image)<\/p>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0ccv2.imread()\u51fd\u6570\u7528\u4e8e\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0ccv2.imshow()\u51fd\u6570\u7528\u4e8e\u5728\u7a97\u53e3\u4e2d\u663e\u793a\u56fe\u50cf\uff0ccv2.waitKey(0)\u51fd\u6570\u7528\u4e8e\u7b49\u5f85\u952e\u76d8\u8f93\u5165\uff0ccv2.destroyAllWindows()\u51fd\u6570\u7528\u4e8e\u5173\u95ed\u6240\u6709\u7a97\u53e3\u3002<\/p>\n<\/p>\n
\u5904\u7406\u56fe\u50cf<\/strong><\/p>\n
\u5728\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u50cf\u540e\uff0c\u53ef\u4ee5\u5bf9\u56fe\u50cf\u8fdb\u884c\u5404\u79cd\u5904\u7406\u64cd\u4f5c\uff0c\u4f8b\u5982\u7070\u5ea6\u8f6c\u6362\u3001\u8fb9\u7f18\u68c0\u6d4b\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u5904\u7406\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
\u7070\u5ea6\u8f6c\u6362<\/strong><\/p>\n
\u5c06\u5f69\u8272\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u5e38\u89c1\u64cd\u4f5c\u3002\u53ef\u4ee5\u4f7f\u7528cv2.cvtColor()\u51fd\u6570\u8fdb\u884c\u7070\u5ea6\u8f6c\u6362\uff1a<\/p>\n<\/p>\n
# \u7070\u5ea6\u8f6c\u6362<\/p>\n
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
cv2.imshow('Gray Image', gray_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fb9\u7f18\u68c0\u6d4b<\/strong><\/p>\n
\u8fb9\u7f18\u68c0\u6d4b\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u5e38\u89c1\u7684\u64cd\u4f5c\u4e4b\u4e00\u3002\u53ef\u4ee5\u4f7f\u7528Canny\u8fb9\u7f18\u68c0\u6d4b\u7b97\u6cd5\u8fdb\u884c\u8fb9\u7f18\u68c0\u6d4b\uff1a<\/p>\n<\/p>\n
# \u8fb9\u7f18\u68c0\u6d4b<\/p>\n
edges = cv2.Canny(gray_image, 100, 200)<\/p>\n
cv2.imshow('Edges', edges)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4ece\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u4e2d\u7684cv2\u5e93\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\uff1a<\/p>\n<\/p>\n
\u4e00\u3001\u5b89\u88c5\u4e0e\u5bfc\u5165OpenCV\u5e93
\u4e8c\u3001\u8bfb\u53d6\u4e0e\u663e\u793a\u56fe\u50cf
\u4e09\u3001\u56fe\u50cf\u5904\u7406\u57fa\u7840\u64cd\u4f5c
\u56db\u3001\u9ad8\u7ea7\u56fe\u50cf\u5904\u7406\u64cd\u4f5c
\u4e94\u3001\u56fe\u50cf\u4fdd\u5b58\u4e0e\u8f93\u51fa
\u516d\u3001\u7efc\u5408\u5b9e\u4f8b\u5e94\u7528<\/p>\n<\/p>\n
\u4e00\u3001\u5b89\u88c5\u4e0e\u5bfc\u5165OpenCV\u5e93<\/h3>\n<\/p>\n
\u8981\u4f7f\u7528OpenCV\u5e93\uff0c\u9996\u5148\u9700\u8981\u5728Python\u73af\u5883\u4e2d\u5b89\u88c5\u8be5\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u6765\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u6210\u529f\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165cv2\u5e93\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6\u4e0e\u663e\u793a\u56fe\u50cf<\/h3>\n<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/p>\n
OpenCV\u63d0\u4f9b\u4e86cv2.imread()\u51fd\u6570\u7528\u4e8e\u8bfb\u53d6\u56fe\u50cf\uff0c\u652f\u6301\u591a\u79cd\u56fe\u50cf\u683c\u5f0f\uff08\u5982JPEG\u3001PNG\u3001BMP\u7b49\uff09\u3002\u53ef\u4ee5\u9009\u62e9\u8bfb\u53d6\u5f69\u8272\u56fe\u50cf\u6216\u7070\u5ea6\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
# \u8bfb\u53d6\u5f69\u8272\u56fe\u50cf<\/p>\n
image = cv2.imread('image.jpg', cv2.IMREAD_COLOR)<\/p>\n
\u8bfb\u53d6\u7070\u5ea6\u56fe\u50cf<\/strong><\/h2>\n
gray_image = cv2.imread('image.jpg', cv2.IMREAD_GRAYSCALE)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u663e\u793a\u56fe\u50cf<\/strong><\/p>\n
\u8bfb\u53d6\u56fe\u50cf\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528cv2.imshow()\u51fd\u6570\u5728\u7a97\u53e3\u4e2d\u663e\u793a\u56fe\u50cf\u3002\u4f7f\u7528cv2.waitKey()\u51fd\u6570\u7b49\u5f85\u952e\u76d8\u8f93\u5165\uff0c\u5e76\u4f7f\u7528cv2.destroyAllWindows()\u51fd\u6570\u5173\u95ed\u7a97\u53e3\uff1a<\/p>\n<\/p>\n
cv2.imshow('Image', image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u56fe\u50cf\u5904\u7406\u57fa\u7840\u64cd\u4f5c<\/h3>\n<\/p>\n
\u989c\u8272\u7a7a\u95f4\u8f6c\u6362<\/strong><\/p>\n
OpenCV\u63d0\u4f9b\u4e86cv2.cvtColor()\u51fd\u6570\u7528\u4e8e\u5728\u4e0d\u540c\u989c\u8272\u7a7a\u95f4\u4e4b\u95f4\u8fdb\u884c\u8f6c\u6362\u3002\u5e38\u89c1\u7684\u989c\u8272\u7a7a\u95f4\u8f6c\u6362\u5305\u62ecBGR\u5230\u7070\u5ea6\u3001BGR\u5230HSV\u7b49\uff1a<\/p>\n<\/p>\n
# BGR\u5230\u7070\u5ea6<\/p>\n
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
BGR\u5230HSV<\/strong><\/h2>\n
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56fe\u50cf\u5e73\u6ed1<\/strong><\/p>\n
\u56fe\u50cf\u5e73\u6ed1\uff08\u6216\u6a21\u7cca\uff09\u662f\u51cf\u5c11\u56fe\u50cf\u566a\u58f0\u548c\u7ec6\u8282\u7684\u5e38\u89c1\u64cd\u4f5c\u3002\u53ef\u4ee5\u4f7f\u7528cv2.GaussianBlur()\u51fd\u6570\u8fdb\u884c\u9ad8\u65af\u6a21\u7cca\uff1a<\/p>\n<\/p>\n
# \u9ad8\u65af\u6a21\u7cca<\/p>\n
blurred_image = cv2.GaussianBlur(image, (5, 5), 0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fb9\u7f18\u68c0\u6d4b<\/strong><\/p>\n
\u8fb9\u7f18\u68c0\u6d4b\u662f\u68c0\u6d4b\u56fe\u50cf\u4e2d\u663e\u8457\u8fb9\u7f18\u7684\u64cd\u4f5c\u3002\u53ef\u4ee5\u4f7f\u7528cv2.Canny()\u51fd\u6570\u8fdb\u884cCanny\u8fb9\u7f18\u68c0\u6d4b\uff1a<\/p>\n<\/p>\n
# Canny\u8fb9\u7f18\u68c0\u6d4b<\/p>\n
edges = cv2.Canny(gray_image, 100, 200)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u9ad8\u7ea7\u56fe\u50cf\u5904\u7406\u64cd\u4f5c<\/h3>\n<\/p>\n
\u56fe\u50cf\u8f6e\u5ed3\u68c0\u6d4b<\/strong><\/p>\n
\u8f6e\u5ed3\u68c0\u6d4b\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u5e38\u89c1\u7684\u64cd\u4f5c\u4e4b\u4e00\uff0c\u53ef\u4ee5\u7528\u4e8e\u68c0\u6d4b\u56fe\u50cf\u4e2d\u7684\u7269\u4f53\u8f6e\u5ed3\u3002\u53ef\u4ee5\u4f7f\u7528cv2.findContours()\u51fd\u6570\u68c0\u6d4b\u8f6e\u5ed3\uff0c\u5e76\u4f7f\u7528cv2.drawContours()\u51fd\u6570\u7ed8\u5236\u8f6e\u5ed3\uff1a<\/p>\n<\/p>\n
# \u8f6e\u5ed3\u68c0\u6d4b<\/p>\n
contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)<\/p>\n
\u7ed8\u5236\u8f6e\u5ed3<\/strong><\/h2>\n
cv2.drawContours(image, contours, -1, (0, 255, 0), 2)<\/p>\n
cv2.imshow('Contours', image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56fe\u50cf\u5f62\u6001\u5b66\u64cd\u4f5c<\/strong><\/p>\n
\u56fe\u50cf\u5f62\u6001\u5b66\u64cd\u4f5c\u5305\u62ec\u8150\u8680\u3001\u81a8\u80c0\u3001\u5f00\u8fd0\u7b97\u3001\u95ed\u8fd0\u7b97\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528cv2.erode()\u3001cv2.dilate()\u3001cv2.morphologyEx()\u7b49\u51fd\u6570\u8fdb\u884c\u5f62\u6001\u5b66\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
# \u8150\u8680\u64cd\u4f5c<\/p>\n
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))<\/p>\n
eroded_image = cv2.erode(gray_image, kernel, iterations=1)<\/p>\n
\u81a8\u80c0\u64cd\u4f5c<\/strong><\/h2>\n
dilated_image = cv2.dilate(gray_image, kernel, iterations=1)<\/p>\n
\u5f00\u8fd0\u7b97\uff08\u5148\u8150\u8680\u540e\u81a8\u80c0\uff09<\/strong><\/h2>\n
opened_image = cv2.morphologyEx(gray_image, cv2.MORPH_OPEN, kernel)<\/p>\n
\u95ed\u8fd0\u7b97\uff08\u5148\u81a8\u80c0\u540e\u8150\u8680\uff09<\/strong><\/h2>\n
closed_image = cv2.morphologyEx(gray_image, cv2.MORPH_CLOSE, kernel)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56fe\u50cf\u53d8\u6362<\/strong><\/p>\n
\u56fe\u50cf\u53d8\u6362\u5305\u62ec\u65cb\u8f6c\u3001\u7f29\u653e\u3001\u4eff\u5c04\u53d8\u6362\u3001\u900f\u89c6\u53d8\u6362\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528cv2.warpAffine()\u3001cv2.warpPerspective()\u7b49\u51fd\u6570\u8fdb\u884c\u56fe\u50cf\u53d8\u6362\uff1a<\/p>\n<\/p>\n
# \u65cb\u8f6c\u56fe\u50cf<\/p>\n
(h, w) = image.shape[:2]<\/p>\n
center = (w \/\/ 2, h \/\/ 2)<\/p>\n
M = cv2.getRotationMatrix2D(center, 45, 1.0)<\/p>\n
rotated_image = cv2.warpAffine(image, M, (w, h))<\/p>\n
\u7f29\u653e\u56fe\u50cf<\/strong><\/h2>\n
resized_image = cv2.resize(image, (300, 300))<\/p>\n
\u4eff\u5c04\u53d8\u6362<\/strong><\/h2>\n
pts1 = np.float32([[50, 50], [200, 50], [50, 200]])<\/p>\n
pts2 = np.float32([[10, 100], [200, 50], [100, 250]])<\/p>\n
M = cv2.getAffineTransform(pts1, pts2)<\/p>\n
affine_image = cv2.warpAffine(image, M, (w, h))<\/p>\n
\u900f\u89c6\u53d8\u6362<\/strong><\/h2>\n
pts1 = np.float32([[56, 65], [368, 52], [28, 387], [389, 390]])<\/p>\n
pts2 = np.float32([[0, 0], [300, 0], [0, 300], [300, 300]])<\/p>\n
M = cv2.getPerspectiveTransform(pts1, pts2)<\/p>\n
warped_image = cv2.warpPerspective(image, M, (300, 300))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u56fe\u50cf\u4fdd\u5b58\u4e0e\u8f93\u51fa<\/h3>\n<\/p>\n
\u5904\u7406\u5b8c\u56fe\u50cf\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528cv2.imwrite()\u51fd\u6570\u5c06\u56fe\u50cf\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
# \u4fdd\u5b58\u56fe\u50cf<\/p>\n
cv2.imwrite('output.jpg', image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u7efc\u5408\u5b9e\u4f8b\u5e94\u7528<\/h3>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406\uff0c\u6211\u4eec\u901a\u8fc7\u4e00\u4e2a\u7efc\u5408\u5b9e\u4f8b\u6765\u6f14\u793a\u5982\u4f55\u8fdb\u884c\u56fe\u50cf\u8bfb\u53d6\u3001\u7070\u5ea6\u8f6c\u6362\u3001\u8fb9\u7f18\u68c0\u6d4b\u3001\u8f6e\u5ed3\u68c0\u6d4b\u548c\u4fdd\u5b58\u7ed3\u679c\u56fe\u50cf\u3002<\/p>\n<\/p>\n
\u7efc\u5408\u5b9e\u4f8b\uff1a\u8fb9\u7f18\u68c0\u6d4b\u4e0e\u8f6e\u5ed3\u7ed8\u5236<\/strong><\/p>\n<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('image.jpg')<\/p>\n
\u7070\u5ea6\u8f6c\u6362<\/strong><\/h2>\n
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
\u9ad8\u65af\u6a21\u7cca<\/strong><\/h2>\n
blurred_image = cv2.GaussianBlur(gray_image, (5, 5), 0)<\/p>\n
\u8fb9\u7f18\u68c0\u6d4b<\/strong><\/h2>\n
edges = cv2.Canny(blurred_image, 50, 150)<\/p>\n
\u8f6e\u5ed3\u68c0\u6d4b<\/strong><\/h2>\n
contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)<\/p>\n
\u7ed8\u5236\u8f6e\u5ed3<\/strong><\/h2>\n
cv2.drawContours(image, contours, -1, (0, 255, 0), 2)<\/p>\n
\u663e\u793a\u7ed3\u679c\u56fe\u50cf<\/strong><\/h2>\n
cv2.imshow('Contours', image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
\u4fdd\u5b58\u7ed3\u679c\u56fe\u50cf<\/strong><\/h2>\n
cv2.imwrite('contours_output.jpg', image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u7efc\u5408\u5b9e\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u8bfb\u53d6\u56fe\u50cf\u5e76\u8fdb\u884c\u7070\u5ea6\u8f6c\u6362\uff0c\u7136\u540e\u8fdb\u884c\u9ad8\u65af\u6a21\u7cca\u4ee5\u51cf\u5c11\u566a\u58f0\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u4f7f\u7528Canny\u8fb9\u7f18\u68c0\u6d4b\u7b97\u6cd5\u68c0\u6d4b\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\uff0c\u5e76\u4f7f\u7528findContours()\u51fd\u6570\u68c0\u6d4b\u8fb9\u7f18\u7684\u8f6e\u5ed3\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528drawContours()\u51fd\u6570\u7ed8\u5236\u68c0\u6d4b\u5230\u7684\u8f6e\u5ed3\u5e76\u663e\u793a\u7ed3\u679c\u56fe\u50cf\uff0c\u6700\u540e\u4fdd\u5b58\u7ed3\u679c\u56fe\u50cf\u5230\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u5df2\u7ecf\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Python\u4e2d\u7684cv2\u5e93\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u3002\u8fd9\u4e9b\u57fa\u7840\u64cd\u4f5c\u548c\u9ad8\u7ea7\u64cd\u4f5c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5b9e\u73b0\u5404\u79cd\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u4efb\u52a1\uff0c\u8fdb\u4e00\u6b65\u5e94\u7528\u4e8e\u5b9e\u9645\u9879\u76ee\u4e2d\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5b89\u88c5cv2\u5e93\u4ee5\u4fbf\u5728Python\u4e2d\u4f7f\u7528\uff1f<\/strong>
\u8981\u5728Python\u4e2d\u4f7f\u7528cv2\u5e93\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\u3002\u5728\u7ec8\u7aef\u6216\u547d\u4ee4\u63d0\u793a\u7b26\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff1apip install opencv-python<\/code>\u3002\u5982\u679c\u9700\u8981\u989d\u5916\u7684\u529f\u80fd\uff0c\u4f8b\u5982\u652f\u6301\u89c6\u9891\u5904\u7406\uff0c\u8fd8\u53ef\u4ee5\u5b89\u88c5opencv-python-headless<\/code>\u3002\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u5728Python\u811a\u672c\u4e2d\u6dfb\u52a0import cv2<\/code>\u6765\u5bfc\u5165\u5e93\u3002<\/p>\n
cv2\u5e93\u6709\u54ea\u4e9b\u5e38\u7528\u7684\u529f\u80fd\u548c\u5e94\u7528\uff1f<\/strong>
cv2\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u529f\u80fd\u3002\u5e38\u7528\u7684\u529f\u80fd\u5305\u62ec\u56fe\u50cf\u8bfb\u53d6\u548c\u4fdd\u5b58\u3001\u56fe\u50cf\u5904\u7406\uff08\u5982\u5e73\u6ed1\u3001\u9510\u5316\u548c\u8fb9\u7f18\u68c0\u6d4b\uff09\u3001\u89c6\u9891\u6355\u6349\u548c\u5904\u7406\u3001\u7279\u5f81\u68c0\u6d4b\uff08\u5982SIFT\u3001SURF\u548cORB\uff09\u3001\u56fe\u50cf\u53d8\u6362\uff08\u5982\u65cb\u8f6c\u3001\u7f29\u653e\u3001\u88c1\u526a\uff09\u7b49\u3002\u5b83\u8fd8\u53ef\u4ee5\u7528\u4e8e\u673a\u5668\u5b66\u4e60<\/a>\u548c\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\uff0c\u4f8b\u5982\u5bf9\u8c61\u68c0\u6d4b\u548c\u4eba\u8138\u8bc6\u522b\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528cv2\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u50cf\uff1f<\/strong>
\u4f7f\u7528cv2\u8bfb\u53d6\u56fe\u50cf\u975e\u5e38\u7b80\u5355\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528cv2.imread('image_path')<\/code>\u51fd\u6570\u8bfb\u53d6\u56fe\u50cf\uff0cimage_path<\/code>\u662f\u56fe\u50cf\u6587\u4ef6\u7684\u8def\u5f84\u3002\u8bfb\u53d6\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528cv2.imshow('window_name', image)<\/code>\u663e\u793a\u56fe\u50cf\uff0c\u5176\u4e2dwindow_name<\/code>\u662f\u7a97\u53e3\u7684\u540d\u79f0\u3002\u4e3a\u4e86\u4fdd\u6301\u7a97\u53e3\u6253\u5f00\uff0c\u4f7f\u7528cv2.waitKey(0)<\/code>\u7b49\u5f85\u7528\u6237\u6309\u952e\uff0c\u7136\u540e\u4f7f\u7528cv2.destroyAllWindows()<\/code>\u5173\u95ed\u6240\u6709\u7a97\u53e3\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u4f7f\u7528python\u4e2d\u7684cv2 \u5728Python\u4e2d\u4f7f\u7528cv2\u5e93\uff08\u5373OpenCV\uff09\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u65f6\uff0c […]","protected":false},"author":3,"featured_media":1088977,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1088975"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1088975"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1088975\/revisions"}],"predecessor-version":[{"id":1088978,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1088975\/revisions\/1088978"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1088977"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1088975"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1088975"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1088975"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}