{"id":1038876,"date":"2024-12-31T12:27:47","date_gmt":"2024-12-31T04:27:47","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1038876.html"},"modified":"2024-12-31T12:27:50","modified_gmt":"2024-12-31T04:27:50","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e5%9b%be%e5%83%8f%e5%8f%98%e6%88%90%e6%89%8b%e7%bb%98%e7%94%bb","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1038876.html","title":{"rendered":"Python\u5982\u4f55\u5c06\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b"},"content":{"rendered":"

\"Python\u5982\u4f55\u5c06\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b\"<\/p>\n

Python\u5c06\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b\u7684\u65b9\u6cd5<\/strong>\uff1a\u53ef\u4ee5\u4f7f\u7528OpenCV\u3001Pillow\u3001scikit-image\u7b49\u5e93\uff0c\u5229\u7528\u56fe\u50cf\u5904\u7406\u7b97\u6cd5\u8fdb\u884c\u8fb9\u7f18\u68c0\u6d4b\u3001\u989c\u8272\u8f6c\u6362\u7b49\u64cd\u4f5c\u6765\u5b9e\u73b0\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u6765\u5c06\u56fe\u50cf\u8f6c\u6362\u6210\u624b\u7ed8\u753b\u6548\u679c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528OpenCV\u5b9e\u73b0\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b<\/p>\n<\/p>\n

OpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528OpenCV\u4e2d\u7684\u8fb9\u7f18\u68c0\u6d4b\u548c\u989c\u8272\u8f6c\u6362\u529f\u80fd\u6765\u5b9e\u73b0\u624b\u7ed8\u753b\u6548\u679c\u3002<\/p>\n<\/p>\n

\u5b89\u88c5OpenCV<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86OpenCV\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u56fe\u50cf\u3002\u4f7f\u7528OpenCV\u7684imread<\/code>\u51fd\u6570\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u3002<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('path_to_image.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/h3>\n<\/p>\n
\u5c06\u5f69\u8272\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u662f\u624b\u7ed8\u6548\u679c\u7684\u7b2c\u4e00\u6b65\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528cvtColor<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n
# \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/p>\n
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u53cd\u8f6c\u56fe\u50cf<\/h3>\n<\/p>\n
\u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf\u7684\u50cf\u7d20\u503c\uff0c\u4f7f\u5f97\u6d45\u8272\u90e8\u5206\u53d8\u4e3a\u6df1\u8272\uff0c\u6df1\u8272\u90e8\u5206\u53d8\u4e3a\u6d45\u8272\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf<\/p>\n
inverted_image = cv2.bitwise_not(gray_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u9ad8\u65af\u6a21\u7cca<\/h3>\n<\/p>\n
\u5bf9\u53cd\u8f6c\u540e\u7684\u56fe\u50cf\u8fdb\u884c\u9ad8\u65af\u6a21\u7cca\u5904\u7406\uff0c\u8fd9\u6709\u52a9\u4e8e\u521b\u5efa\u624b\u7ed8\u6548\u679c\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
# \u9ad8\u65af\u6a21\u7cca<\/p>\n
blurred_image = cv2.GaussianBlur(inverted_image, (21, 21), sigmaX=0, sigmaY=0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/h3>\n<\/p>\n
\u901a\u8fc7\u5c06\u6a21\u7cca\u540e\u7684\u56fe\u50cf\u518d\u6b21\u53cd\u8f6c\uff0c\u5e76\u4e0e\u539f\u59cb\u7070\u5ea6\u56fe\u50cf\u8fdb\u884c\u6df7\u5408\uff0c\u5f97\u5230\u624b\u7ed8\u6548\u679c\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u6a21\u7cca\u56fe\u50cf<\/p>\n
inverted_blurred_image = cv2.bitwise_not(blurred_image)<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/strong><\/h2>\n
sketch_image = cv2.divide(gray_image, inverted_blurred_image, scale=256.0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u663e\u793a\u548c\u4fdd\u5b58\u56fe\u50cf<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u4f7f\u7528OpenCV\u7684imshow<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\uff0c\u5e76\u4f7f\u7528imwrite<\/code>\u51fd\u6570\u4fdd\u5b58\u56fe\u50cf\u3002<\/p>\n<\/p>\n
# \u663e\u793a\u56fe\u50cf<\/p>\n
cv2.imshow('Sketch Image', sketch_image)<\/p>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
\u4fdd\u5b58\u56fe\u50cf<\/strong><\/h2>\n
cv2.imwrite('sketch_image.jpg', sketch_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528Pillow\u5b9e\u73b0\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b<\/p>\n<\/p>\n
Pillow\u662fPython\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528Pillow\u4e2d\u7684\u6ee4\u955c\u548c\u56fe\u50cf\u5904\u7406\u65b9\u6cd5\u6765\u5b9e\u73b0\u624b\u7ed8\u753b\u6548\u679c\u3002<\/p>\n<\/p>\n
\u5b89\u88c5Pillow<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Pillow\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install pillow<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/h3>\n<\/p>\n
\u4f7f\u7528Pillow\u7684Image<\/code>\u6a21\u5757\u8bfb\u53d6\u56fe\u50cf\u3002<\/p>\n<\/p>\n
from PIL import Image, ImageOps, ImageFilter<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = Image.open('path_to_image.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/h3>\n<\/p>\n
\u5c06\u5f69\u8272\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u3002<\/p>\n<\/p>\n
# \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/p>\n
gray_image = ImageOps.grayscale(image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u53cd\u8f6c\u56fe\u50cf<\/h3>\n<\/p>\n
\u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf\u7684\u50cf\u7d20\u503c\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf<\/p>\n
inverted_image = ImageOps.invert(gray_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u9ad8\u65af\u6a21\u7cca<\/h3>\n<\/p>\n
\u5bf9\u53cd\u8f6c\u540e\u7684\u56fe\u50cf\u8fdb\u884c\u9ad8\u65af\u6a21\u7cca\u5904\u7406\u3002<\/p>\n<\/p>\n
# \u9ad8\u65af\u6a21\u7cca<\/p>\n
blurred_image = inverted_image.filter(ImageFilter.GaussianBlur(radius=10))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/h3>\n<\/p>\n
\u901a\u8fc7\u5c06\u6a21\u7cca\u540e\u7684\u56fe\u50cf\u518d\u6b21\u53cd\u8f6c\uff0c\u5e76\u4e0e\u539f\u59cb\u7070\u5ea6\u56fe\u50cf\u8fdb\u884c\u6df7\u5408\uff0c\u5f97\u5230\u624b\u7ed8\u6548\u679c\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u6a21\u7cca\u56fe\u50cf<\/p>\n
inverted_blurred_image = ImageOps.invert(blurred_image)<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/strong><\/h2>\n
sketch_image = Image.blend(gray_image, inverted_blurred_image, alpha=0.5)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u663e\u793a\u548c\u4fdd\u5b58\u56fe\u50cf<\/h3>\n<\/p>\n
\u4f7f\u7528Pillow\u7684show<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u50cf\uff0c\u5e76\u4f7f\u7528save<\/code>\u65b9\u6cd5\u4fdd\u5b58\u56fe\u50cf\u3002<\/p>\n<\/p>\n
# \u663e\u793a\u56fe\u50cf<\/p>\n
sketch_image.show()<\/p>\n
\u4fdd\u5b58\u56fe\u50cf<\/strong><\/h2>\n
sketch_image.save('sketch_image.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528scikit-image\u5b9e\u73b0\u56fe\u50cf\u53d8\u6210\u624b\u7ed8\u753b<\/p>\n<\/p>\n
scikit-image\u662f\u4e00\u4e2a\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u7684Python\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u56fe\u50cf\u5904\u7406\u7b97\u6cd5\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528scikit-image\u4e2d\u7684\u6ee4\u955c\u548c\u8f6c\u6362\u51fd\u6570\u6765\u5b9e\u73b0\u624b\u7ed8\u753b\u6548\u679c\u3002<\/p>\n<\/p>\n
\u5b89\u88c5scikit-image<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86scikit-image\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install scikit-image<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/h3>\n<\/p>\n
\u4f7f\u7528scikit-image\u7684io<\/code>\u6a21\u5757\u8bfb\u53d6\u56fe\u50cf\u3002<\/p>\n<\/p>\n
from skimage import io, color<\/p>\n
import numpy as np<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = io.imread('path_to_image.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/h3>\n<\/p>\n
\u5c06\u5f69\u8272\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u3002<\/p>\n<\/p>\n
# \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/p>\n
gray_image = color.rgb2gray(image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u53cd\u8f6c\u56fe\u50cf<\/h3>\n<\/p>\n
\u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf\u7684\u50cf\u7d20\u503c\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u7070\u5ea6\u56fe\u50cf<\/p>\n
inverted_image = np.invert(gray_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u9ad8\u65af\u6a21\u7cca<\/h3>\n<\/p>\n
\u5bf9\u53cd\u8f6c\u540e\u7684\u56fe\u50cf\u8fdb\u884c\u9ad8\u65af\u6a21\u7cca\u5904\u7406\u3002<\/p>\n<\/p>\n
from skimage.filters import gaussian<\/p>\n
\u9ad8\u65af\u6a21\u7cca<\/strong><\/h2>\n
blurred_image = gaussian(inverted_image, sigma=10)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/h3>\n<\/p>\n
\u901a\u8fc7\u5c06\u6a21\u7cca\u540e\u7684\u56fe\u50cf\u518d\u6b21\u53cd\u8f6c\uff0c\u5e76\u4e0e\u539f\u59cb\u7070\u5ea6\u56fe\u50cf\u8fdb\u884c\u6df7\u5408\uff0c\u5f97\u5230\u624b\u7ed8\u6548\u679c\u3002<\/p>\n<\/p>\n
# \u53cd\u8f6c\u6a21\u7cca\u56fe\u50cf<\/p>\n
inverted_blurred_image = np.invert(blurred_image)<\/p>\n
\u521b\u5efa\u624b\u7ed8\u6548\u679c<\/strong><\/h2>\n
sketch_image = gray_image \/ inverted_blurred_image<\/p>\n
sketch_image = np.clip(sketch_image, 0, 1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u663e\u793a\u548c\u4fdd\u5b58\u56fe\u50cf<\/h3>\n<\/p>\n
\u4f7f\u7528scikit-image\u7684io<\/code>\u6a21\u5757\u663e\u793a\u548c\u4fdd\u5b58\u56fe\u50cf\u3002<\/p>\n<\/p>\n
# \u663e\u793a\u56fe\u50cf<\/p>\n
io.imshow(sketch_image)<\/p>\n
io.show()<\/p>\n
\u4fdd\u5b58\u56fe\u50cf<\/strong><\/h2>\n
io.imsave('sketch_image.jpg', sketch_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u901a\u8fc7\u4f7f\u7528OpenCV\u3001Pillow\u548cscikit-image\u7b49\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06\u56fe\u50cf\u8f6c\u6362\u6210\u624b\u7ed8\u753b\u6548\u679c\u3002\u6bcf\u4e2a\u5e93\u90fd\u6709\u5176\u72ec\u7279\u7684\u529f\u80fd\u548c\u4f18\u52bf\uff0c\u9009\u62e9\u9002\u5408\u81ea\u5df1\u7684\u5e93\u8fdb\u884c\u56fe\u50cf\u5904\u7406\uff0c\u53ef\u4ee5\u63d0\u9ad8\u5f00\u53d1\u6548\u7387\u548c\u6548\u679c\u3002<\/p>\n<\/p>\n
\u65e0\u8bba\u4f60\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u90fd\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u53c2\u6570\u548c\u6dfb\u52a0\u66f4\u591a\u7684\u56fe\u50cf\u5904\u7406\u6b65\u9aa4\uff0c\u8fdb\u4e00\u6b65\u4f18\u5316\u624b\u7ed8\u753b\u6548\u679c\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff0c\u80fd\u591f\u8ba9\u4f60\u5728Python\u56fe\u50cf\u5904\u7406\u9886\u57df\u6709\u6240\u6536\u83b7\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u624b\u7ed8\u6548\u679c\uff1f<\/strong>
\u8981\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u624b\u7ed8\u6548\u679c\uff0c\u53ef\u4ee5\u4f7f\u7528OpenCV\u548cPIL\u5e93\u3002\u901a\u8fc7\u8fb9\u7f18\u68c0\u6d4b\u548c\u56fe\u50cf\u8fc7\u6ee4\u6280\u672f\uff0c\u60a8\u53ef\u4ee5\u5b9e\u73b0\u624b\u7ed8\u98ce\u683c\u3002\u9996\u5148\uff0c\u52a0\u8f7d\u56fe\u50cf\u5e76\u5c06\u5176\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\uff0c\u7136\u540e\u5e94\u7528\u8fb9\u7f18\u68c0\u6d4b\u7b97\u6cd5\uff08\u5982Canny\u7b97\u6cd5\uff09\uff0c\u63a5\u7740\u4f7f\u7528\u4e00\u4e9b\u56fe\u50cf\u5904\u7406\u65b9\u6cd5\uff08\u5982\u6a21\u7cca\u6216\u9608\u503c\u5904\u7406\uff09\u6765\u521b\u5efa\u624b\u7ed8\u6548\u679c\u3002\u6700\u540e\uff0c\u4fdd\u5b58\u5904\u7406\u540e\u7684\u56fe\u50cf\u3002<\/p>\n
\u5728Python\u4e2d\u8f6c\u6362\u56fe\u50cf\u4e3a\u624b\u7ed8\u753b\u9700\u8981\u54ea\u4e9b\u5e93\uff1f<\/strong>
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