{"id":1184468,"date":"2025-01-15T19:26:45","date_gmt":"2025-01-15T11:26:45","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1184468.html"},"modified":"2025-01-15T19:26:49","modified_gmt":"2025-01-15T11:26:49","slug":"python%e4%bb%a3%e7%a0%81%e5%a6%82%e4%bd%95%e5%ae%9e%e7%8e%b0%e6%89%a3%e5%9b%be","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1184468.html","title":{"rendered":"python\u4ee3\u7801\u5982\u4f55\u5b9e\u73b0\u6263\u56fe"},"content":{"rendered":"

\"python\u4ee3\u7801\u5982\u4f55\u5b9e\u73b0\u6263\u56fe\"<\/p>\n

Python\u4ee3\u7801\u5b9e\u73b0\u6263\u56fe\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528OpenCV\u5e93\u548cNumPy\u5e93\u6765\u5b8c\u6210\uff0c\u6838\u5fc3\u6b65\u9aa4\u5305\u62ec\uff1a\u8bfb\u53d6\u56fe\u50cf\u3001\u8f6c\u6362\u989c\u8272\u7a7a\u95f4\u3001\u521b\u5efa\u63a9\u7801\u3001\u5e94\u7528\u63a9\u7801\u4ee5\u53ca\u4fdd\u5b58\u7ed3\u679c\u3002<\/strong>\u5176\u4e2d\uff0c\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u662f\u5173\u952e\u7684\u4e00\u6b65\u3002\u6211\u4eec\u53ef\u4ee5\u8be6\u7ec6\u89e3\u91ca\u5176\u4e2d\u7684\u521b\u5efa\u63a9\u7801\u6b65\u9aa4\u3002<\/p>\n<\/p>\n

\u5728\u521b\u5efa\u63a9\u7801\u7684\u8fc7\u7a0b\u4e2d\uff0c\u9700\u8981\u9009\u62e9\u56fe\u50cf\u4e2d\u7684\u7279\u5b9a\u989c\u8272\u8303\u56f4\u6765\u751f\u6210\u4e00\u4e2a\u4e8c\u503c\u63a9\u7801\uff0c\u8fd9\u4e2a\u63a9\u7801\u5c06\u6307\u793a\u56fe\u50cf\u4e2d\u7684\u54ea\u4e9b\u50cf\u7d20\u662f\u524d\u666f\uff08\u9700\u8981\u4fdd\u7559\u7684\u90e8\u5206\uff09\u4ee5\u53ca\u54ea\u4e9b\u50cf\u7d20\u662f\u80cc\u666f\uff08\u9700\u8981\u53bb\u9664\u7684\u90e8\u5206\uff09\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u8fd9\u4e2a\u63a9\u7801\u6765\u63d0\u53d6\u56fe\u50cf\u4e2d\u7684\u524d\u666f\u90e8\u5206\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u5b89\u88c5\u4e0e\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/strong><\/h2>\n

\u5728\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86OpenCV\u548cNumPy\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\u8fd9\u4e24\u4e2a\u5e93\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\u5728Python\u4ee3\u7801\u4e2d\u5bfc\u5165\u5b83\u4eec\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u8981\u5904\u7406\u7684\u56fe\u50cf\u3002\u5047\u8bbe\u56fe\u50cf\u6587\u4ef6\u540d\u4e3ainput.jpg<\/code>\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8bfb\u53d6\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
image = cv2.imread('input.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
cv2.imread()<\/code>\u51fd\u6570\u4f1a\u8bfb\u53d6\u56fe\u50cf\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u4e00\u4e2aNumPy\u6570\u7ec4\u4e2d\uff0c\u65b9\u4fbf\u540e\u7eed\u5904\u7406\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u8f6c\u6362\u989c\u8272\u7a7a\u95f4<\/strong><\/h2>\n
\u4e3a\u4e86\u66f4\u5bb9\u6613\u5730\u8fdb\u884c\u989c\u8272\u5206\u5272\uff0c\u6211\u4eec\u5c06\u56fe\u50cf\u4eceBGR\u989c\u8272\u7a7a\u95f4\u8f6c\u6362\u4e3aHSV\u989c\u8272\u7a7a\u95f4\u3002HSV\u989c\u8272\u7a7a\u95f4\u66f4\u9002\u5408\u8fdb\u884c\u989c\u8272\u5206\u5272\uff0c\u56e0\u4e3a\u5b83\u5c06\u989c\u8272\u4fe1\u606f\u4e0e\u4eae\u5ea6\u4fe1\u606f\u5206\u5f00\u4e86\uff1a<\/p>\n<\/p>\n
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u521b\u5efa\u63a9\u7801<\/strong><\/h2>\n
\u5728HSV\u989c\u8272\u7a7a\u95f4\u4e2d\u9009\u62e9\u4e00\u4e2a\u989c\u8272\u8303\u56f4\u6765\u521b\u5efa\u63a9\u7801\u3002\u5047\u8bbe\u6211\u4eec\u8981\u6263\u9664\u7684\u56fe\u50cf\u80cc\u666f\u662f\u7eff\u8272\u7684\uff0c\u53ef\u4ee5\u5b9a\u4e49\u7eff\u8272\u7684HSV\u8303\u56f4\uff1a<\/p>\n<\/p>\n
lower_green = np.array([35, 100, 100])<\/p>\n
upper_green = np.array([85, 255, 255])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528cv2.inRange()<\/code>\u51fd\u6570\u521b\u5efa\u63a9\u7801\uff1a<\/p>\n<\/p>\n
mask = cv2.inRange(hsv_image, lower_green, upper_green)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6b64\u65f6\uff0cmask<\/code>\u662f\u4e00\u4e2a\u4e8c\u503c\u56fe\u50cf\uff0c\u5176\u4e2d\u767d\u8272\u50cf\u7d20\u8868\u793a\u7eff\u8272\u533a\u57df\uff0c\u9ed1\u8272\u50cf\u7d20\u8868\u793a\u975e\u7eff\u8272\u533a\u57df\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u5e94\u7528\u63a9\u7801<\/strong><\/h2>\n
\u4f7f\u7528\u63a9\u7801\u63d0\u53d6\u56fe\u50cf\u7684\u524d\u666f\u90e8\u5206\uff1a<\/p>\n<\/p>\n
foreground = cv2.bitwise_and(image, image, mask=~mask)<\/p>\n
<\/code><\/pre>\n<\/p>\n
cv2.bitwise_and()<\/code>\u51fd\u6570\u5c06\u63a9\u7801\u5e94\u7528\u5230\u539f\u59cb\u56fe\u50cf\u4e0a\uff0c\u63d0\u53d6\u51fa\u524d\u666f\u90e8\u5206\u3002\u8fd9\u91cc\u4f7f\u7528~mask<\/code>\u53d6\u53cd\u63a9\u7801\uff0c\u4ee5\u4fdd\u7559\u975e\u7eff\u8272\u533a\u57df\u3002<\/p>\n<\/p>\n
\u516d\u3001\u4fdd\u5b58\u7ed3\u679c<\/strong><\/h2>\n
\u6700\u540e\uff0c\u5c06\u5904\u7406\u540e\u7684\u56fe\u50cf\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
cv2.imwrite('output.png', foreground)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u5176\u4ed6\u65b9\u6cd5\u4e0e\u6539\u8fdb<\/strong><\/h2>\n
\u9664\u4e86\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u8fd8\u53ef\u4ee5\u4f7f\u7528\u5176\u4ed6\u6280\u672f\u6765\u6539\u8fdb\u6263\u56fe\u6548\u679c\u3002\u4f8b\u5982\uff0c\u4f7f\u7528GrabCut\u7b97\u6cd5\u8fdb\u884c\u524d\u666f\u63d0\u53d6\uff1a<\/p>\n<\/p>\n
mask = np.zeros(image.shape[:2], np.uint8)<\/p>\n
bgdModel = np.zeros((1, 65), np.float64)<\/p>\n
fgdModel = np.zeros((1, 65), np.float64)<\/p>\n
rect = (50, 50, image.shape[1]-50, image.shape[0]-50)<\/p>\n
cv2.grabCut(image, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)<\/p>\n
mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')<\/p>\n
foreground = image * mask2[:, :, np.newaxis]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e0a\u8ff0\u4ee3\u7801\u4f7f\u7528GrabCut\u7b97\u6cd5\u8fdb\u884c\u524d\u666f\u63d0\u53d6\uff0c\u53ef\u4ee5\u66f4\u7cbe\u786e\u5730\u5206\u79bb\u524d\u666f\u548c\u80cc\u666f\u3002<\/p>\n<\/p>\n
\u516b\u3001\u603b\u7ed3<\/strong><\/h2>\n
\u672c\u6587\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Python\u548cOpenCV\u5e93\u5b9e\u73b0\u56fe\u50cf\u6263\u56fe\u7684\u57fa\u672c\u65b9\u6cd5\u3002\u901a\u8fc7\u8bfb\u53d6\u56fe\u50cf\u3001\u8f6c\u6362\u989c\u8272\u7a7a\u95f4\u3001\u521b\u5efa\u63a9\u7801\u3001\u5e94\u7528\u63a9\u7801\u4ee5\u53ca\u4fdd\u5b58\u7ed3\u679c\uff0c\u53ef\u4ee5\u5b9e\u73b0\u57fa\u672c\u7684\u56fe\u50cf\u6263\u56fe\u529f\u80fd\u3002\u6b64\u5916\uff0c\u8fd8\u53ef\u4ee5\u4f7f\u7528\u66f4\u9ad8\u7ea7\u7684\u7b97\u6cd5\u5982GrabCut\u6765\u8fdb\u4e00\u6b65\u6539\u8fdb\u6263\u56fe\u6548\u679c\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff0c\u80fd\u591f\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u5e94\u7528\u8fd9\u4e9b\u6280\u672f\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002<\/p>\n<\/p>\n
\u4e5d\u3001\u5b8c\u6574\u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
\u4ee5\u4e0b\u662f\u5b8c\u6574\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5305\u542b\u4e86\u6240\u6709\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('input.jpg')<\/p>\n
\u8f6c\u6362\u4e3aHSV\u989c\u8272\u7a7a\u95f4<\/strong><\/h2>\n
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)<\/p>\n
\u5b9a\u4e49\u7eff\u8272\u7684HSV\u8303\u56f4<\/strong><\/h2>\n
lower_green = np.array([35, 100, 100])<\/p>\n
upper_green = np.array([85, 255, 255])<\/p>\n
\u521b\u5efa\u63a9\u7801<\/strong><\/h2>\n
mask = cv2.inRange(hsv_image, lower_green, upper_green)<\/p>\n
\u63d0\u53d6\u524d\u666f<\/strong><\/h2>\n
foreground = cv2.bitwise_and(image, image, mask=~mask)<\/p>\n
\u4fdd\u5b58\u7ed3\u679c<\/strong><\/h2>\n
cv2.imwrite('output.png', foreground)<\/p>\n
\u4f7f\u7528GrabCut\u7b97\u6cd5\u6539\u8fdb\u6263\u56fe\u6548\u679c<\/strong><\/h2>\n
mask = np.zeros(image.shape[:2], np.uint8)<\/p>\n
bgdModel = np.zeros((1, 65), np.float64)<\/p>\n
fgdModel = np.zeros((1, 65), np.float64)<\/p>\n
rect = (50, 50, image.shape[1]-50, image.shape[0]-50)<\/p>\n
cv2.grabCut(image, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)<\/p>\n
mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')<\/p>\n
foreground = image * mask2[:, :, np.newaxis]<\/p>\n
\u4fdd\u5b58\u6539\u8fdb\u540e\u7684\u7ed3\u679c<\/strong><\/h2>\n
cv2.imwrite('output_grabcut.png', foreground)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u4ee3\u7801\uff0c\u53ef\u4ee5\u5b9e\u73b0\u57fa\u672c\u7684\u56fe\u50cf\u6263\u56fe\u529f\u80fd\uff0c\u5e76\u4f7f\u7528GrabCut\u7b97\u6cd5\u8fdb\u4e00\u6b65\u6539\u8fdb\u6263\u56fe\u6548\u679c\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff0c\u80fd\u591f\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u5e94\u7528\u8fd9\u4e9b\u6280\u672f\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u6263\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
\u6263\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u5305\u62ec\u8bfb\u53d6\u56fe\u50cf\u3001\u9009\u62e9\u8981\u4fdd\u7559\u7684\u533a\u57df\u3001\u521b\u5efa\u63a9\u819c\u4ee5\u53ca\u5e94\u7528\u8be5\u63a9\u819c\u6765\u63d0\u53d6\u76ee\u6807\u5bf9\u8c61\u3002\u5e38\u7528\u7684\u5e93\u6709OpenCV\u548cPIL\u3002\u4f60\u53ef\u4ee5\u5148\u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u50cf\uff0c\u7136\u540e\u901a\u8fc7\u56fe\u50cf\u5904\u7406\u6280\u672f\uff08\u5982\u9608\u503c\u5904\u7406\u6216\u8fb9\u7f18\u68c0\u6d4b\uff09\u83b7\u53d6\u63a9\u819c\uff0c\u6700\u540e\u4f7f\u7528NumPy\u5c06\u63a9\u819c\u5e94\u7528\u4e8e\u539f\u56fe\u50cf\uff0c\u63d0\u53d6\u51fa\u4f60\u60f3\u8981\u7684\u90e8\u5206\u3002<\/p>\n
\u54ea\u4e9bPython\u5e93\u53ef\u4ee5\u5e2e\u52a9\u5b9e\u73b0\u6263\u56fe\u529f\u80fd\uff1f<\/strong>
\u5728Python\u4e2d\uff0cOpenCV\u548cPIL\uff08Pillow\uff09\u662f\u5b9e\u73b0\u6263\u56fe\u7684\u70ed\u95e8\u9009\u62e9\u3002OpenCV\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u9002\u5408\u590d\u6742\u7684\u56fe\u50cf\u64cd\u4f5c\uff0c\u800cPIL\u5219\u66f4\u52a0\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5feb\u901f\u5904\u7406\u548c\u663e\u793a\u56fe\u50cf\u3002\u6b64\u5916\uff0cNumPy\u5e93\u4e5f\u53ef\u4ee5\u7528\u4e8e\u9ad8\u6548\u7684\u6570\u7ec4\u8fd0\u7b97\uff0c\u5e2e\u52a9\u4f60\u66f4\u7075\u6d3b\u5730\u5904\u7406\u56fe\u50cf\u6570\u636e\u3002<\/p>\n
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