{"id":1097431,"date":"2025-01-08T15:11:49","date_gmt":"2025-01-08T07:11:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1097431.html"},"modified":"2025-01-08T15:11:51","modified_gmt":"2025-01-08T07:11:51","slug":"python%e5%a6%82%e4%bd%95%e6%b1%82%e5%9b%be%e7%89%87%e7%9a%84%e5%9d%90%e6%a0%87%e5%80%bc-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1097431.html","title":{"rendered":"python\u5982\u4f55\u6c42\u56fe\u7247\u7684\u5750\u6807\u503c"},"content":{"rendered":"

\"python\u5982\u4f55\u6c42\u56fe\u7247\u7684\u5750\u6807\u503c\"<\/p>\n

\u8981\u5728Python\u4e2d\u6c42\u53d6\u56fe\u7247\u7684\u5750\u6807\u503c\uff0c\u53ef\u4ee5\u4f7f\u7528\u51e0\u79cd\u4e0d\u540c\u7684\u6280\u672f\u548c\u5e93\uff0c\u4f8b\u5982OpenCV\u3001Pillow\u548cNumPy\u7b49\u3002\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3001\u5229\u7528Pillow\u8fdb\u884c\u57fa\u672c\u56fe\u50cf\u64cd\u4f5c\u3001\u7ed3\u5408NumPy\u8fdb\u884c\u77e9\u9635\u8fd0\u7b97<\/strong>\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u63d0\u53d6\u548c\u5904\u7406\u56fe\u50cf\u5750\u6807\u3002\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5de5\u5177\u548c\u6280\u672f\u6765\u6c42\u53d6\u56fe\u7247\u7684\u5750\u6807\u503c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406<\/h3>\n<\/p>\n

OpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u5e7f\u6cdb\u5e94\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u3002\u4f7f\u7528OpenCV\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u5206\u6790\u56fe\u50cf\u6570\u636e\u3002<\/p>\n<\/p>\n

1. \u8bfb\u53d6\u56fe\u50cf<\/h4>\n<\/p>\n

\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5OpenCV\u5e93\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
\u63a5\u4e0b\u6765\uff0c\u901a\u8fc7OpenCV\u8bfb\u53d6\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('path_to_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
2. \u83b7\u53d6\u56fe\u50cf\u7684\u5c3a\u5bf8\u548c\u901a\u9053\u4fe1\u606f<\/h4>\n<\/p>\n
\u5728\u56fe\u50cf\u5904\u7406\u4e2d\uff0c\u4e86\u89e3\u56fe\u50cf\u7684\u5c3a\u5bf8\u548c\u901a\u9053\u4fe1\u606f\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684shape<\/code>\u5c5e\u6027\u83b7\u53d6\u8fd9\u4e9b\u4fe1\u606f\uff1a<\/p>\n<\/p>\n
height, width, channels = image.shape<\/p>\n
print(f'Height: {height}, Width: {width}, Channels: {channels}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u83b7\u53d6\u50cf\u7d20\u503c<\/h4>\n<\/p>\n
\u5728OpenCV\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u56fe\u50cf\u7684\u6570\u7ec4\u7d22\u5f15\u83b7\u53d6\u50cf\u7d20\u503c\u3002\u4f8b\u5982\uff0c\u83b7\u53d6(100, 100)\u5904\u7684\u50cf\u7d20\u503c\uff1a<\/p>\n<\/p>\n
pixel_value = image[100, 100]<\/p>\n
print(f'Pixel value at (100, 100): {pixel_value}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u56fe\u50cf\u5750\u6807\u53d8\u6362<\/h4>\n<\/p>\n
\u5728\u56fe\u50cf\u5904\u7406\u4e2d\uff0c\u5750\u6807\u53d8\u6362\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u64cd\u4f5c\u3002OpenCV\u63d0\u4f9b\u4e86\u591a\u79cd\u53d8\u6362\u51fd\u6570\uff0c\u4f8b\u5982\u4eff\u5c04\u53d8\u6362\u548c\u900f\u89c6\u53d8\u6362\u3002<\/p>\n<\/p>\n
\u4eff\u5c04\u53d8\u6362<\/h5>\n<\/p>\n
\u4eff\u5c04\u53d8\u6362\u662f\u4e00\u79cd\u7ebf\u6027\u53d8\u6362\uff0c\u5305\u62ec\u5e73\u79fb\u3001\u65cb\u8f6c\u3001\u7f29\u653e\u548c\u526a\u5207\u3002\u53ef\u4ee5\u4f7f\u7528cv2.getAffineTransform<\/code>\u548ccv2.warpAffine<\/code>\u51fd\u6570\u8fdb\u884c\u4eff\u5c04\u53d8\u6362\uff1a<\/p>\n<\/p>\n
# \u5b9a\u4e49\u4eff\u5c04\u53d8\u6362\u7684\u4e09\u4e2a\u70b9<\/p>\n
pts1 = np.float32([[50, 50], [200, 50], [50, 200]])<\/p>\n
pts2 = np.float32([[10, 100], [200, 50], [100, 250]])<\/p>\n
\u83b7\u53d6\u4eff\u5c04\u53d8\u6362\u77e9\u9635<\/strong><\/h2>\n
M = cv2.getAffineTransform(pts1, pts2)<\/p>\n
\u5e94\u7528\u4eff\u5c04\u53d8\u6362<\/strong><\/h2>\n
transformed_image = cv2.warpAffine(image, M, (width, height))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u5229\u7528Pillow\u8fdb\u884c\u57fa\u672c\u56fe\u50cf\u64cd\u4f5c<\/h3>\n<\/p>\n
Pillow\u662f\u4e00\u4e2a\u6d41\u884c\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u64cd\u4f5c\u529f\u80fd\u3002\u53ef\u4ee5\u4f7f\u7528Pillow\u8fdb\u884c\u57fa\u672c\u7684\u56fe\u50cf\u64cd\u4f5c\uff0c\u4f8b\u5982\u8bfb\u53d6\u3001\u4fdd\u5b58\u548c\u5904\u7406\u56fe\u50cf\u3002<\/p>\n<\/p>\n
1. \u8bfb\u53d6\u56fe\u50cf<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5Pillow\u5e93\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
\u63a5\u4e0b\u6765\uff0c\u901a\u8fc7Pillow\u8bfb\u53d6\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
from PIL import Image<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = Image.open('path_to_image.jpg')<\/p>\n
\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n
image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u83b7\u53d6\u56fe\u50cf\u5c3a\u5bf8<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528Pillow\u7684size<\/code>\u5c5e\u6027\u83b7\u53d6\u56fe\u50cf\u7684\u5c3a\u5bf8\uff1a<\/p>\n<\/p>\n
width, height = image.size<\/p>\n
print(f'Width: {width}, Height: {height}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u83b7\u53d6\u50cf\u7d20\u503c<\/h4>\n<\/p>\n
\u5728Pillow\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7getpixel<\/code>\u65b9\u6cd5\u83b7\u53d6\u50cf\u7d20\u503c\u3002\u4f8b\u5982\uff0c\u83b7\u53d6(100, 100)\u5904\u7684\u50cf\u7d20\u503c\uff1a<\/p>\n<\/p>\n
pixel_value = image.getpixel((100, 100))<\/p>\n
print(f'Pixel value at (100, 100): {pixel_value}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u56fe\u50cf\u5750\u6807\u53d8\u6362<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528Pillow\u8fdb\u884c\u57fa\u672c\u7684\u56fe\u50cf\u5750\u6807\u53d8\u6362\uff0c\u4f8b\u5982\u65cb\u8f6c\u3001\u7f29\u653e\u548c\u88c1\u526a\u3002<\/p>\n<\/p>\n
\u65cb\u8f6c<\/h5>\n<\/p>\n
\u4f7f\u7528rotate<\/code>\u65b9\u6cd5\u65cb\u8f6c\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
rotated_image = image.rotate(45)<\/p>\n
rotated_image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7f29\u653e<\/h5>\n<\/p>\n
\u4f7f\u7528resize<\/code>\u65b9\u6cd5\u7f29\u653e\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
resized_image = image.resize((width \/\/ 2, height \/\/ 2))<\/p>\n
resized_image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u88c1\u526a<\/h5>\n<\/p>\n
\u4f7f\u7528crop<\/code>\u65b9\u6cd5\u88c1\u526a\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
cropped_image = image.crop((50, 50, 200, 200))<\/p>\n
cropped_image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u7ed3\u5408NumPy\u8fdb\u884c\u77e9\u9635\u8fd0\u7b97<\/h3>\n<\/p>\n
NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u503c\u8ba1\u7b97\u5e93\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u77e9\u9635\u8fd0\u7b97\u548c\u6570\u636e\u5904\u7406\u3002\u7ed3\u5408NumPy\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5904\u7406\u56fe\u50cf\u6570\u636e\u3002<\/p>\n<\/p>\n
1. \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528NumPy\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u6570\u7ec4\u8fdb\u884c\u5904\u7406\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4<\/strong><\/h2>\n
image_array = np.array(image)<\/p>\n
\u83b7\u53d6\u56fe\u50cf\u7684\u5c3a\u5bf8<\/strong><\/h2>\n
height, width, channels = image_array.shape<\/p>\n
print(f'Height: {height}, Width: {width}, Channels: {channels}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u83b7\u53d6\u50cf\u7d20\u503c<\/h4>\n<\/p>\n
\u5728NumPy\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u6570\u7ec4\u7d22\u5f15\u83b7\u53d6\u50cf\u7d20\u503c\u3002\u4f8b\u5982\uff0c\u83b7\u53d6(100, 100)\u5904\u7684\u50cf\u7d20\u503c\uff1a<\/p>\n<\/p>\n
pixel_value = image_array[100, 100]<\/p>\n
print(f'Pixel value at (100, 100): {pixel_value}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u56fe\u50cf\u5750\u6807\u53d8\u6362<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528NumPy\u8fdb\u884c\u56fe\u50cf\u5750\u6807\u53d8\u6362\uff0c\u4f8b\u5982\u65cb\u8f6c\u3001\u5e73\u79fb\u548c\u7f29\u653e\u3002<\/p>\n<\/p>\n
\u65cb\u8f6c<\/h5>\n<\/p>\n
\u4f7f\u7528NumPy\u8fdb\u884c\u56fe\u50cf\u65cb\u8f6c\uff1a<\/p>\n<\/p>\n
def rotate_image(image, angle):<\/p>\n
    # \u83b7\u53d6\u56fe\u50cf\u7684\u4e2d\u5fc3<\/p>\n
    center = (image.shape[1] \/\/ 2, image.shape[0] \/\/ 2)<\/p>\n
    # \u83b7\u53d6\u65cb\u8f6c\u77e9\u9635<\/p>\n
    M = cv2.getRotationMatrix2D(center, angle, 1.0)<\/p>\n
    # \u5e94\u7528\u65cb\u8f6c<\/p>\n
    rotated_image = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))<\/p>\n
    return rotated_image<\/p>\n
rotated_image = rotate_image(image_array, 45)<\/p>\n
cv2.imshow('Rotated Image', rotated_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5e73\u79fb<\/h5>\n<\/p>\n
\u4f7f\u7528NumPy\u8fdb\u884c\u56fe\u50cf\u5e73\u79fb\uff1a<\/p>\n<\/p>\n
def translate_image(image, tx, ty):<\/p>\n
    # \u83b7\u53d6\u5e73\u79fb\u77e9\u9635<\/p>\n
    M = np.float32([[1, 0, tx], [0, 1, ty]])<\/p>\n
    # \u5e94\u7528\u5e73\u79fb<\/p>\n
    translated_image = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))<\/p>\n
    return translated_image<\/p>\n
translated_image = translate_image(image_array, 50, 100)<\/p>\n
cv2.imshow('Translated Image', translated_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7f29\u653e<\/h5>\n<\/p>\n
\u4f7f\u7528NumPy\u8fdb\u884c\u56fe\u50cf\u7f29\u653e\uff1a<\/p>\n<\/p>\n
def scale_image(image, fx, fy):<\/p>\n
    # \u5e94\u7528\u7f29\u653e<\/p>\n
    scaled_image = cv2.resize(image, None, fx=fx, fy=fy, interpolation=cv2.INTER_LINEAR)<\/p>\n
    return scaled_image<\/p>\n
scaled_image = scale_image(image_array, 0.5, 0.5)<\/p>\n
cv2.imshow('Scaled Image', scaled_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u7efc\u5408\u5b9e\u4f8b<\/h3>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u4ecb\u7ecd\u7684\u6280\u672f\uff0c\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u7efc\u5408\u5b9e\u4f8b\uff0c\u8bfb\u53d6\u56fe\u50cf\u5e76\u8fdb\u884c\u4e00\u7cfb\u5217\u7684\u56fe\u50cf\u5904\u7406\u64cd\u4f5c\uff0c\u6700\u540e\u8f93\u51fa\u5904\u7406\u540e\u7684\u56fe\u50cf\u548c\u5750\u6807\u503c\u3002<\/p>\n<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
from PIL import Image<\/p>\n
def main():<\/p>\n
    # \u8bfb\u53d6\u56fe\u50cf<\/p>\n
    image_path = 'path_to_image.jpg'<\/p>\n
    image = cv2.imread(image_path)<\/p>\n
    pil_image = Image.open(image_path)<\/p>\n
    # \u83b7\u53d6\u56fe\u50cf\u5c3a\u5bf8<\/p>\n
    height, width, channels = image.shape<\/p>\n
    print(f'Original Image - Height: {height}, Width: {width}, Channels: {channels}')<\/p>\n
    # \u83b7\u53d6\u50cf\u7d20\u503c<\/p>\n
    pixel_value = image[100, 100]<\/p>\n
    print(f'Pixel value at (100, 100): {pixel_value}')<\/p>\n
    # \u56fe\u50cf\u65cb\u8f6c<\/p>\n
    rotated_image = cv2.rotate(image, cv2.ROTATE_90_CLOCKWISE)<\/p>\n
    # \u56fe\u50cf\u5e73\u79fb<\/p>\n
    translated_image = translate_image(image, 50, 100)<\/p>\n
    # \u56fe\u50cf\u7f29\u653e<\/p>\n
    scaled_image = scale_image(image, 0.5, 0.5)<\/p>\n
    # \u663e\u793a\u5904\u7406\u540e\u7684\u56fe\u50cf<\/p>\n
    cv2.imshow('Rotated Image', rotated_image)<\/p>\n
    cv2.imshow('Translated Image', translated_image)<\/p>\n
    cv2.imshow('Scaled Image', scaled_image)<\/p>\n
    cv2.waitKey(0)<\/p>\n
    cv2.destroyAllWindows()<\/p>\n
def translate_image(image, tx, ty):<\/p>\n
    M = np.float32([[1, 0, tx], [0, 1, ty]])<\/p>\n
    translated_image = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))<\/p>\n
    return translated_image<\/p>\n
def scale_image(image, fx, fy):<\/p>\n
    scaled_image = cv2.resize(image, None, fx=fx, fy=fy, interpolation=cv2.INTER_LINEAR)<\/p>\n
    return scaled_image<\/p>\n
if __name__ == "__main__":<\/p>\n
    main()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u4ee3\u7801\uff0c\u53ef\u4ee5\u8bfb\u53d6\u56fe\u50cf\u5e76\u8fdb\u884c\u65cb\u8f6c\u3001\u5e73\u79fb\u548c\u7f29\u653e\u64cd\u4f5c\uff0c\u6700\u540e\u663e\u793a\u5904\u7406\u540e\u7684\u56fe\u50cf\u548c\u76f8\u5e94\u7684\u5750\u6807\u503c\u3002\u8fd9\u6837\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u7406\u89e3\u548c\u638c\u63e1\u5982\u4f55\u5728Python\u4e2d\u6c42\u53d6\u56fe\u7247\u7684\u5750\u6807\u503c\u5e76\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u56fe\u7247\u7684\u5750\u6807\u503c\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u56fe\u50cf\u5904\u7406\u5e93\u5982OpenCV\u6216PIL\uff08Pillow\uff09\u6765\u8bfb\u53d6\u548c\u5904\u7406\u56fe\u7247\u3002\u901a\u8fc7\u8fd9\u4e9b\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u83b7\u53d6\u56fe\u50cf\u7684\u5c3a\u5bf8\u548c\u50cf\u7d20\u5750\u6807\u3002\u4f8b\u5982\uff0c\u4f7f\u7528OpenCV\u7684cv2.imread()<\/code>\u51fd\u6570\u8bfb\u53d6\u56fe\u7247\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7image.shape<\/code>\u83b7\u53d6\u56fe\u50cf\u7684\u9ad8\u548c\u5bbd\uff0c\u4ece\u800c\u786e\u5b9a\u5750\u6807\u503c\u7684\u8303\u56f4\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u83b7\u53d6\u7279\u5b9a\u50cf\u7d20\u7684RGB\u503c\uff1f<\/strong>
\u8981\u83b7\u53d6\u7279\u5b9a\u5750\u6807\u5904\u50cf\u7d20\u7684RGB\u503c\uff0c\u53ef\u4ee5\u4f7f\u7528PIL\u5e93\u7684Image.open()<\/code>\u51fd\u6570\u52a0\u8f7d\u56fe\u50cf\uff0c\u5e76\u4f7f\u7528getpixel()<\/code>\u65b9\u6cd5\u6765\u83b7\u53d6\u6307\u5b9a\u5750\u6807\u7684RGB\u503c\u3002\u4f8b\u5982\uff0c\u901a\u8fc7img.getpixel((x, y))<\/code>\u53ef\u4ee5\u76f4\u63a5\u83b7\u53d6\u5750\u6807(x, y)\u5904\u7684RGB\u503c\u3002\u8fd9\u5bf9\u4e8e\u56fe\u50cf\u5206\u6790\u548c\u5904\u7406\u975e\u5e38\u6709\u7528\u3002<\/p>\n
\u5728Python\u4e2d\uff0c\u5982\u4f55\u6839\u636e\u5750\u6807\u503c\u88c1\u526a\u56fe\u7247\uff1f<\/strong>
\u53ef\u4ee5\u4f7f\u7528PIL\u5e93\u4e2d\u7684crop()<\/code>\u65b9\u6cd5\u6839\u636e\u6307\u5b9a\u7684\u5750\u6807\u503c\u88c1\u526a\u56fe\u7247\u3002\u4f60\u9700\u8981\u5b9a\u4e49\u4e00\u4e2a\u77e9\u5f62\u533a\u57df\u7684\u5750\u6807\uff0c\u8be5\u533a\u57df\u7531\u5de6\u4e0a\u89d2\u548c\u53f3\u4e0b\u89d2\u7684\u5750\u6807\u70b9\u786e\u5b9a\u3002\u4f8b\u5982\uff0cimg.crop((left, upper, right, lower))<\/code>\u80fd\u591f\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u56fe\u50cf\uff0c\u8be5\u56fe\u50cf\u53ea\u5305\u542b\u6307\u5b9a\u533a\u57df\u3002\u8fd9\u6837\u7684\u64cd\u4f5c\u975e\u5e38\u9002\u5408\u5904\u7406\u56fe\u50cf\u4e2d\u7684\u7279\u5b9a\u533a\u57df\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u5728Python\u4e2d\u6c42\u53d6\u56fe\u7247\u7684\u5750\u6807\u503c\uff0c\u53ef\u4ee5\u4f7f\u7528\u51e0\u79cd\u4e0d\u540c\u7684\u6280\u672f\u548c\u5e93\uff0c\u4f8b\u5982OpenCV\u3001Pillow\u548cNumPy\u7b49\u3002 […]","protected":false},"author":3,"featured_media":1097436,"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\/1097431"}],"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=1097431"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1097431\/revisions"}],"predecessor-version":[{"id":1097442,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1097431\/revisions\/1097442"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1097436"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1097431"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1097431"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1097431"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}