{"id":1163565,"date":"2025-01-15T14:56:43","date_gmt":"2025-01-15T06:56:43","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1163565.html"},"modified":"2025-01-15T14:56:45","modified_gmt":"2025-01-15T06:56:45","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e8%af%bb%e5%8f%96%e5%9b%be%e7%89%87%e4%bf%a1%e6%81%af","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1163565.html","title":{"rendered":"\u5982\u4f55\u7528python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\"<\/p>\n

\u5982\u4f55\u7528Python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u5982\u5229\u7528Pillow\u5e93\u3001OpenCV\u5e93\u3001scikit-image\u5e93\u7b49\u3002<\/strong> \u8fd9\u4e9b\u5e93\u5404\u6709\u4f18\u52a3\uff0c\u4f46Pillow\u5e93\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5927\u591a\u6570\u57fa\u7840\u56fe\u50cf\u5904\u7406\u9700\u6c42\u3002\u4f7f\u7528Pillow\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u3001\u4fee\u6539\u56fe\u7247\u3001\u4fdd\u5b58\u56fe\u7247<\/strong>\uff0c\u800cOpenCV\u5219\u9002\u7528\u4e8e\u66f4\u590d\u6742\u548c\u9ad8\u6548\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u3002\u63a5\u4e0b\u6765\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u3002<\/p>\n<\/p>\n

\u4e00\u3001PILLOW\u5e93<\/strong><\/p>\n<\/p>\n

Pillow\u662fPython Imaging Library\u7684\u5206\u652f\uff0c\u652f\u6301\u591a\u79cd\u56fe\u50cf\u683c\u5f0f\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Pillow\u5e93<\/h3>\n<\/p>\n

\u5728\u4f7f\u7528Pillow\u5e93\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5b89\u88c5\u5b83\u3002\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
2\u3001\u8bfb\u53d6\u56fe\u7247<\/h3>\n<\/p>\n
\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u7247\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u4f7f\u7528Image\u6a21\u5757\u7684open\u51fd\u6570\uff1a<\/p>\n<\/p>\n
from PIL import Image<\/p>\n
\u6253\u5f00\u56fe\u7247<\/strong><\/h2>\n
image = Image.open('example.jpg')<\/p>\n
\u663e\u793a\u56fe\u7247<\/strong><\/h2>\n
image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u83b7\u53d6\u56fe\u7247\u4fe1\u606f<\/h3>\n<\/p>\n
Pillow\u5e93\u63d0\u4f9b\u4e86\u83b7\u53d6\u56fe\u7247\u4fe1\u606f\u7684\u5404\u79cd\u65b9\u6cd5\uff0c\u4f8b\u5982\u56fe\u7247\u7684\u683c\u5f0f\u3001\u5c3a\u5bf8\u3001\u8272\u5f69\u6a21\u5f0f\u7b49\uff1a<\/p>\n<\/p>\n
# \u83b7\u53d6\u56fe\u7247\u683c\u5f0f<\/p>\n
format = image.format<\/p>\n
print(f"Format: {format}")<\/p>\n
\u83b7\u53d6\u56fe\u7247\u5c3a\u5bf8<\/strong><\/h2>\n
size = image.size<\/p>\n
print(f"Size: {size}")<\/p>\n
\u83b7\u53d6\u56fe\u7247\u8272\u5f69\u6a21\u5f0f<\/strong><\/h2>\n
mode = image.mode<\/p>\n
print(f"Mode: {mode}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5904\u7406\u56fe\u7247<\/h3>\n<\/p>\n
Pillow\u5e93\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u4f8b\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u7b49\uff1a<\/p>\n<\/p>\n
# \u88c1\u526a\u56fe\u7247<\/p>\n
cropped_image = image.crop((100, 100, 400, 400))<\/p>\n
cropped_image.show()<\/p>\n
\u65cb\u8f6c\u56fe\u7247<\/strong><\/h2>\n
rotated_image = image.rotate(45)<\/p>\n
rotated_image.show()<\/p>\n
\u8c03\u6574\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
resized_image = image.resize((200, 200))<\/p>\n
resized_image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u4fdd\u5b58\u56fe\u7247<\/h3>\n<\/p>\n
\u5904\u7406\u5b8c\u56fe\u7247\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528save\u51fd\u6570\u5c06\u56fe\u7247\u4fdd\u5b58\u4e3a\u4e0d\u540c\u7684\u683c\u5f0f\uff1a<\/p>\n<\/p>\n
# \u4fdd\u5b58\u56fe\u7247<\/p>\n
resized_image.save('resized_image.jpg')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001OPENCV\u5e93<\/strong><\/p>\n<\/p>\n
OpenCV\uff08Open Source Computer Vision Library\uff09\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u673a\u5668\u5b66\u4e60<\/a>\u8f6f\u4ef6\u5e93\uff0c\u5177\u6709\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5OpenCV\u5e93<\/h3>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5OpenCV\u5e93\uff1a<\/p>\n<\/p>\n
pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6\u56fe\u7247<\/h3>\n<\/p>\n
\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u7247\u4e5f\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u4f7f\u7528cv2\u6a21\u5757\u7684imread\u51fd\u6570\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
image = cv2.imread('example.jpg')<\/p>\n
\u663e\u793a\u56fe\u7247<\/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
3\u3001\u83b7\u53d6\u56fe\u7247\u4fe1\u606f<\/h3>\n<\/p>\n
OpenCV\u5e93\u63d0\u4f9b\u4e86\u83b7\u53d6\u56fe\u7247\u4fe1\u606f\u7684\u5404\u79cd\u65b9\u6cd5\uff0c\u4f8b\u5982\u56fe\u7247\u7684\u5c3a\u5bf8\u3001\u901a\u9053\u6570\u7b49\uff1a<\/p>\n<\/p>\n
# \u83b7\u53d6\u56fe\u7247\u5c3a\u5bf8<\/p>\n
height, width, channels = image.shape<\/p>\n
print(f"Height: {height}, Width: {width}, Channels: {channels}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5904\u7406\u56fe\u7247<\/h3>\n<\/p>\n
OpenCV\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u4f8b\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u3001\u8f6c\u6362\u8272\u5f69\u7a7a\u95f4\u7b49\uff1a<\/p>\n<\/p>\n
# \u88c1\u526a\u56fe\u7247<\/p>\n
cropped_image = image[100:400, 100:400]<\/p>\n
cv2.imshow('Cropped Image', cropped_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
\u65cb\u8f6c\u56fe\u7247<\/strong><\/h2>\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
cv2.imshow('Rotated Image', rotated_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
\u8c03\u6574\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
resized_image = cv2.resize(image, (200, 200))<\/p>\n
cv2.imshow('Resized Image', resized_image)<\/p>\n
cv2.waitKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
\u8f6c\u6362\u8272\u5f69\u7a7a\u95f4<\/strong><\/h2>\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
5\u3001\u4fdd\u5b58\u56fe\u7247<\/h3>\n<\/p>\n
\u5904\u7406\u5b8c\u56fe\u7247\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528imwrite\u51fd\u6570\u5c06\u56fe\u7247\u4fdd\u5b58\u4e3a\u4e0d\u540c\u7684\u683c\u5f0f\uff1a<\/p>\n<\/p>\n
# \u4fdd\u5b58\u56fe\u7247<\/p>\n
cv2.imwrite('resized_image.jpg', resized_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001SCIKIT-IMAGE\u5e93<\/strong><\/p>\n<\/p>\n
scikit-image\u662f\u4e00\u4e2a\u57fa\u4e8eNumPy\u6784\u5efa\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u9002\u7528\u4e8e\u5b66\u672f\u7814\u7a76\u548c\u79d1\u5b66\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5scikit-image\u5e93<\/h3>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5scikit-image\u5e93\uff1a<\/p>\n<\/p>\n
pip install scikit-image<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6\u56fe\u7247<\/h3>\n<\/p>\n
\u4f7f\u7528scikit-image\u5e93\u8bfb\u53d6\u56fe\u7247\u4e5f\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u4f7f\u7528io\u6a21\u5757\u7684imread\u51fd\u6570\uff1a<\/p>\n<\/p>\n
from skimage import io<\/p>\n
\u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
image = io.imread('example.jpg')<\/p>\n
\u663e\u793a\u56fe\u7247<\/strong><\/h2>\n
io.imshow(image)<\/p>\n
io.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u83b7\u53d6\u56fe\u7247\u4fe1\u606f<\/h3>\n<\/p>\n
scikit-image\u5e93\u63d0\u4f9b\u4e86\u83b7\u53d6\u56fe\u7247\u4fe1\u606f\u7684\u5404\u79cd\u65b9\u6cd5\uff0c\u4f8b\u5982\u56fe\u7247\u7684\u5c3a\u5bf8\u3001\u901a\u9053\u6570\u7b49\uff1a<\/p>\n<\/p>\n
# \u83b7\u53d6\u56fe\u7247\u5c3a\u5bf8<\/p>\n
height, width, channels = image.shape<\/p>\n
print(f"Height: {height}, Width: {width}, Channels: {channels}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5904\u7406\u56fe\u7247<\/h3>\n<\/p>\n
scikit-image\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u4f8b\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u3001\u8f6c\u6362\u8272\u5f69\u7a7a\u95f4\u7b49\uff1a<\/p>\n<\/p>\n
from skimage.transform import resize, rotate<\/p>\n
\u88c1\u526a\u56fe\u7247<\/strong><\/h2>\n
cropped_image = image[100:400, 100:400]<\/p>\n
io.imshow(cropped_image)<\/p>\n
io.show()<\/p>\n
\u65cb\u8f6c\u56fe\u7247<\/strong><\/h2>\n
rotated_image = rotate(image, 45)<\/p>\n
io.imshow(rotated_image)<\/p>\n
io.show()<\/p>\n
\u8c03\u6574\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
resized_image = resize(image, (200, 200))<\/p>\n
io.imshow(resized_image)<\/p>\n
io.show()<\/p>\n
\u8f6c\u6362\u8272\u5f69\u7a7a\u95f4<\/strong><\/h2>\n
from skimage.color import rgb2gray<\/p>\n
gray_image = rgb2gray(image)<\/p>\n
io.imshow(gray_image)<\/p>\n
io.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u4fdd\u5b58\u56fe\u7247<\/h3>\n<\/p>\n
\u5904\u7406\u5b8c\u56fe\u7247\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528io\u6a21\u5757\u7684imsave\u51fd\u6570\u5c06\u56fe\u7247\u4fdd\u5b58\u4e3a\u4e0d\u540c\u7684\u683c\u5f0f\uff1a<\/p>\n<\/p>\n
# \u4fdd\u5b58\u56fe\u7247<\/p>\n
io.imsave('resized_image.jpg', resized_image)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u603b\u7ed3<\/strong><\/p>\n<\/p>\n
\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u6709\u591a\u79cd\u65b9\u5f0f\uff0c\u5e38\u7528\u7684\u5e93\u6709Pillow\u3001OpenCV\u548cscikit-image\u3002<\/strong> Pillow\u5e93\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5927\u591a\u6570\u57fa\u7840\u56fe\u50cf\u5904\u7406\u9700\u6c42\uff1bOpenCV\u9002\u7528\u4e8e\u66f4\u590d\u6742\u548c\u9ad8\u6548\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\uff1bscikit-image\u9002\u7528\u4e8e\u5b66\u672f\u7814\u7a76\u548c\u79d1\u5b66\u8ba1\u7b97\u3002<\/strong> \u9009\u62e9\u5408\u9002\u7684\u5e93\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u8fdb\u884c\u9009\u62e9<\/strong>\uff0c\u4ee5\u4e0a\u4ecb\u7ecd\u4e86\u5982\u4f55\u5b89\u88c5\u3001\u8bfb\u53d6\u3001\u83b7\u53d6\u4fe1\u606f\u3001\u5904\u7406\u548c\u4fdd\u5b58\u56fe\u7247\uff0c\u80fd\u591f\u6ee1\u8db3\u7edd\u5927\u591a\u6570\u56fe\u50cf\u5904\u7406\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u83b7\u53d6\u56fe\u7247\u7684\u57fa\u672c\u4fe1\u606f\uff1f<\/strong>
\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u5e93\u6765\u5b9e\u73b0\u3002\u6700\u5e38\u7528\u7684\u5e93\u662fPillow\uff08PIL\u7684\u4e00\u4e2a\u5206\u652f\uff09\uff0c\u53ef\u4ee5\u901a\u8fc7Image.open()<\/code>\u51fd\u6570\u6253\u5f00\u56fe\u7247\u6587\u4ef6\uff0c\u7136\u540e\u4f7f\u7528Image.info<\/code>\u5c5e\u6027\u83b7\u53d6\u56fe\u7247\u7684\u5143\u6570\u636e\u3002\u6b64\u5916\uff0cImage.size<\/code>\u53ef\u4ee5\u83b7\u53d6\u56fe\u7247\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\uff0cImage.format<\/code>\u53ef\u4ee5\u67e5\u770b\u56fe\u7247\u683c\u5f0f\uff08\u5982JPEG\u3001PNG\u7b49\uff09\u3002\u5b89\u88c5Pillow\u5e93\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u547d\u4ee4pip install Pillow<\/code>\u3002<\/p>\n
\u4f7f\u7528Python\u53ef\u4ee5\u83b7\u53d6\u54ea\u4e9b\u7c7b\u578b\u7684\u56fe\u7247\u4fe1\u606f\uff1f<\/strong>
Python\u53ef\u4ee5\u63d0\u53d6\u591a\u79cd\u56fe\u7247\u4fe1\u606f\uff0c\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u56fe\u7247\u7684\u5bbd\u5ea6\u3001\u9ad8\u5ea6\u3001\u683c\u5f0f\u3001\u989c\u8272\u6a21\u5f0f\u3001\u6587\u4ef6\u5927\u5c0f\u3001\u62cd\u6444\u65f6\u95f4\uff08EXIF\u6570\u636e\uff09\u7b49\u3002\u901a\u8fc7Pillow\u5e93\u53ef\u4ee5\u8f7b\u677e\u8bbf\u95ee\u8fd9\u4e9b\u4fe1\u606f\uff0c\u800c\u5bf9\u4e8e\u66f4\u590d\u6742\u7684EXIF\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528piexif<\/code>\u5e93\u6765\u63d0\u53d6\u66f4\u8be6\u7ec6\u7684\u62cd\u6444\u53c2\u6570\u548c\u8bbe\u7f6e\uff0c\u5982\u66dd\u5149\u65f6\u95f4\u3001ISO\u503c\u7b49\u3002<\/p>\n
\u6211\u5728\u8bfb\u53d6\u56fe\u7247\u4fe1\u606f\u65f6\u9047\u5230\u9519\u8bef\uff0c\u5982\u4f55\u89e3\u51b3\uff1f<\/strong>
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