{"id":1142439,"date":"2025-01-08T22:40:10","date_gmt":"2025-01-08T14:40:10","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1142439.html"},"modified":"2025-01-08T22:40:12","modified_gmt":"2025-01-08T14:40:12","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%81%9a%e4%b8%80%e4%b8%aa%e4%ba%ba%e8%84%b8%e8%af%86%e5%88%ab%e7%99%bb%e5%bd%95","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1142439.html","title":{"rendered":"\u5982\u4f55\u7528python\u505a\u4e00\u4e2a\u4eba\u8138\u8bc6\u522b\u767b\u5f55"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u505a\u4e00\u4e2a\u4eba\u8138\u8bc6\u522b\u767b\u5f55\"<\/p>\n

\u5982\u4f55\u7528Python\u505a\u4e00\u4e2a\u4eba\u8138\u8bc6\u522b\u767b\u5f55<\/strong><\/p>\n<\/p>\n

\u5728\u73b0\u4ee3\u79d1\u6280\u7684\u8fc5\u901f\u53d1\u5c55\u4e2d\uff0c\u4eba\u8138\u8bc6\u522b\u6280\u672f\u5df2\u7ecf\u6210\u4e3a\u4e86\u8eab\u4efd\u9a8c\u8bc1\u548c\u5b89\u5168\u767b\u5f55\u7684\u70ed\u95e8\u9009\u62e9\u3002Python\u7684\u4e30\u5bcc\u5e93\u652f\u6301\u3001OpenCV\u7684\u5f3a\u5927\u529f\u80fd\u3001Dlib\u7684\u9ad8\u6548\u4eba\u8138\u68c0\u6d4b\u3001\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u7684\u6613\u7528\u6027<\/strong>\u4f7f\u5f97\u5728Python\u4e2d\u5b9e\u73b0\u4eba\u8138\u8bc6\u522b\u767b\u5f55\u53d8\u5f97\u76f8\u5bf9\u7b80\u5355\u3002\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5229\u7528\u8fd9\u4e9b\u5de5\u5177\u548c\u6280\u672f\u6765\u6784\u5efa\u4e00\u4e2a\u53ef\u9760\u7684\u4eba\u8138\u8bc6\u522b\u767b\u5f55\u7cfb\u7edf\u3002<\/p>\n<\/p>\n

\u4e00\u3001Python\u7684\u4e30\u5bcc\u5e93\u652f\u6301<\/h3>\n<\/p>\n

Python\u4f5c\u4e3a\u4e00\u79cd\u9ad8\u6548\u4e14\u5e7f\u6cdb\u4f7f\u7528\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u62e5\u6709\u4e30\u5bcc\u7684\u5e93\u6765\u652f\u6301\u4eba\u8138\u8bc6\u522b\u7684\u5b9e\u73b0\u3002OpenCV\u3001Dlib\u3001Face_recognition\u7b49\u5e93\u90fd\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u529f\u80fd\u6765\u8fdb\u884c\u4eba\u8138\u68c0\u6d4b\u548c\u8bc6\u522b\u3002<\/p>\n<\/p>\n

1\u3001OpenCV\u7684\u5f3a\u5927\u529f\u80fd<\/h4>\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\u3002\u5b83\u4e3a\u5b9e\u65f6\u8ba1\u7b97\u673a\u89c6\u89c9\u63d0\u4f9b\u4e86\u6570\u5343\u4e2a\u9ad8\u6548\u7684\u7b97\u6cd5\uff0c\u53ef\u4ee5\u5904\u7406\u56fe\u50cf\u548c\u89c6\u9891\uff0c\u8bc6\u522b\u9762\u90e8\u548c\u7269\u4f53\uff0c\u751a\u81f3\u8fdb\u884c3D\u91cd\u5efa\u3002<\/p>\n<\/p>\n

\u5b89\u88c5\u548c\u57fa\u672c\u4f7f\u7528\uff1a<\/strong><\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
pip install opencv-python-headless<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528OpenCV\u8fdb\u884c\u57fa\u672c\u4eba\u8138\u68c0\u6d4b\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u52a0\u8f7d\u9884\u8bad\u7ec3\u7684\u9762\u90e8\u68c0\u6d4b\u6a21\u578b<\/strong><\/h2>\n
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('path_to_image.jpg')<\/p>\n
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
\u68c0\u6d4b\u9762\u90e8<\/strong><\/h2>\n
faces = face_cascade.detectMultiScale(gray, 1.1, 4)<\/p>\n
\u7ed8\u5236\u77e9\u5f62\u6846\u5728\u68c0\u6d4b\u5230\u7684\u9762\u90e8\u5468\u56f4<\/strong><\/h2>\n
for (x, y, w, h) in faces:<\/p>\n
    cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)<\/p>\n
\u663e\u793a\u7ed3\u679c<\/strong><\/h2>\n
cv2.imshow('Face Detection', image)<\/p>\n
cv2.wAI<\/a>tKey()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001Dlib\u7684\u9ad8\u6548\u4eba\u8138\u68c0\u6d4b<\/h4>\n<\/p>\n
Dlib\u662f\u4e00\u4e2a\u73b0\u4ee3C++\u5de5\u5177\u5305\uff0c\u5305\u542b\u4e86\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u548c\u5de5\u5177\uff0c\u7279\u522b\u662f\u4eba\u8138\u68c0\u6d4b\u548c\u4eba\u8138\u7279\u5f81\u70b9\u63d0\u53d6\u3002Dlib\u5e93\u7684\u6838\u5fc3\u4f18\u52bf\u5728\u4e8e\u5176\u9ad8\u6548\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
\u5b89\u88c5\u548c\u57fa\u672c\u4f7f\u7528\uff1a<\/strong><\/p>\n<\/p>\n
pip install dlib<\/p>\n
pip install face_recognition<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4f7f\u7528Dlib\u8fdb\u884c\u4eba\u8138\u7279\u5f81\u70b9\u68c0\u6d4b\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import dlib<\/p>\n
import cv2<\/p>\n
\u52a0\u8f7d\u9884\u8bad\u7ec3\u7684\u4eba\u8138\u68c0\u6d4b\u6a21\u578b<\/strong><\/h2>\n
detector = dlib.get_frontal_face_detector()<\/p>\n
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')<\/p>\n
\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
image = cv2.imread('path_to_image.jpg')<\/p>\n
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
\u68c0\u6d4b\u9762\u90e8<\/strong><\/h2>\n
faces = detector(gray)<\/p>\n
for face in faces:<\/p>\n
    landmarks = predictor(gray, face)<\/p>\n
    for n in range(0, 68):<\/p>\n
        x = landmarks.part(n).x<\/p>\n
        y = landmarks.part(n).y<\/p>\n
        cv2.circle(image, (x, y), 1, (255, 0, 0), -1)<\/p>\n
\u663e\u793a\u7ed3\u679c<\/strong><\/h2>\n
cv2.imshow('Face Landmarks', image)<\/p>\n
cv2.waitKey()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001Face_recognition\u5e93\u7684\u4f7f\u7528<\/h3>\n<\/p>\n
Face_recognition\u5e93\u662f\u57fa\u4e8eDlib\u7684\u9ad8\u5c42\u6b21\u5e93\uff0c\u7b80\u5316\u4e86\u4eba\u8138\u8bc6\u522b\u7684\u8fc7\u7a0b\u3002\u5b83\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684API\u6765\u8fdb\u884c\u4eba\u8138\u8bc6\u522b\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5\u548c\u57fa\u672c\u4f7f\u7528<\/h4>\n<\/p>\n
\u5b89\u88c5\uff1a<\/strong><\/p>\n<\/p>\n
pip install face_recognition<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4f7f\u7528Face_recognition\u5e93\u8fdb\u884c\u4eba\u8138\u8bc6\u522b\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import face_recognition<\/p>\n
\u52a0\u8f7d\u793a\u4f8b\u56fe\u7247\u5e76\u5b66\u4e60\u5982\u4f55\u8bc6\u522b\u5b83<\/strong><\/h2>\n
known_image = face_recognition.load_image_file("path_to_known_image.jpg")<\/p>\n
known_encoding = face_recognition.face_encodings(known_image)[0]<\/p>\n
\u52a0\u8f7d\u65b0\u56fe\u7247\u5e76\u5c1d\u8bd5\u8bc6\u522b\u5b83<\/strong><\/h2>\n
unknown_image = face_recognition.load_image_file("path_to_unknown_image.jpg")<\/p>\n
unknown_encoding = face_recognition.face_encodings(unknown_image)[0]<\/p>\n
\u6bd4\u8f83\u4eba\u8138<\/strong><\/h2>\n
results = face_recognition.compare_faces([known_encoding], unknown_encoding)<\/p>\n
if results[0]:<\/p>\n
    print("This is the known person.")<\/p>\n
else:<\/p>\n
    print("This is NOT the known person.")<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6574\u5408\u5230\u767b\u5f55\u7cfb\u7edf\u4e2d<\/h4>\n<\/p>\n
\u8981\u5c06\u4eba\u8138\u8bc6\u522b\u6574\u5408\u5230\u767b\u5f55\u7cfb\u7edf\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6570\u636e\u5e93\u6216\u6587\u4ef6\u7cfb\u7edf\u6765\u5b58\u50a8\u7528\u6237\u7684\u9762\u90e8\u7279\u5f81\u7f16\u7801\u3002\u5728\u7528\u6237\u767b\u5f55\u65f6\uff0c\u7cfb\u7edf\u4f1a\u6355\u83b7\u5f53\u524d\u7684\u9762\u90e8\u56fe\u50cf\uff0c\u63d0\u53d6\u7279\u5f81\u7f16\u7801\uff0c\u5e76\u4e0e\u5b58\u50a8\u7684\u7f16\u7801\u8fdb\u884c\u6bd4\u8f83\u3002<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5316\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import face_recognition<\/p>\n
import cv2<\/p>\n
\u52a0\u8f7d\u5df2\u6ce8\u518c\u7528\u6237\u7684\u9762\u90e8\u7279\u5f81\u7f16\u7801<\/strong><\/h2>\n
registered_encodings = {<\/p>\n
    "user1": face_recognition.face_encodings(face_recognition.load_image_file("user1.jpg"))[0],<\/p>\n
    "user2": face_recognition.face_encodings(face_recognition.load_image_file("user2.jpg"))[0]<\/p>\n
}<\/p>\n
\u6355\u83b7\u5f53\u524d\u9762\u90e8\u56fe\u50cf<\/strong><\/h2>\n
video_capture = cv2.VideoCapture(0)<\/p>\n
ret, frame = video_capture.read()<\/p>\n
video_capture.release()<\/p>\n
\u68c0\u6d4b\u5e76\u63d0\u53d6\u5f53\u524d\u9762\u90e8\u7279\u5f81\u7f16\u7801<\/strong><\/h2>\n
current_encoding = face_recognition.face_encodings(frame)[0]<\/p>\n
\u6bd4\u8f83\u5f53\u524d\u9762\u90e8\u7279\u5f81\u7f16\u7801\u4e0e\u5df2\u6ce8\u518c\u7528\u6237<\/strong><\/h2>\n
for user, encoding in registered_encodings.items():<\/p>\n
    results = face_recognition.compare_faces([encoding], current_encoding)<\/p>\n
    if results[0]:<\/p>\n
        print(f"Welcome, {user}!")<\/p>\n
        break<\/p>\n
else:<\/p>\n
    print("Unknown user!")<\/p>\n
\u6e05\u7406\u8d44\u6e90<\/strong><\/h2>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5b9e\u73b0\u767b\u5f55\u754c\u9762<\/h3>\n<\/p>\n
\u4e3a\u4e86\u63d0\u9ad8\u7528\u6237\u4f53\u9a8c\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Tkinter\u6216PyQt\u7b49GUI\u5e93\u6765\u521b\u5efa\u4e00\u4e2a\u53cb\u597d\u7684\u767b\u5f55\u754c\u9762\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528Tkinter\u521b\u5efa\u767b\u5f55\u754c\u9762<\/h4>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4f7f\u7528Tkinter\u521b\u5efa\u7b80\u5355\u767b\u5f55\u754c\u9762\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import tkinter as tk<\/p>\n
from tkinter import messagebox<\/p>\n
import face_recognition<\/p>\n
import cv2<\/p>\n
def capture_image():<\/p>\n
    video_capture = cv2.VideoCapture(0)<\/p>\n
    ret, frame = video_capture.read()<\/p>\n
    video_capture.release()<\/p>\n
    cv2.imwrite("current.jpg", frame)<\/p>\n
def login():<\/p>\n
    capture_image()<\/p>\n
    current_image = face_recognition.load_image_file("current.jpg")<\/p>\n
    current_encoding = face_recognition.face_encodings(current_image)[0]<\/p>\n
    for user, encoding in registered_encodings.items():<\/p>\n
        results = face_recognition.compare_faces([encoding], current_encoding)<\/p>\n
        if results[0]:<\/p>\n
            messagebox.showinfo("Login Success", f"Welcome, {user}!")<\/p>\n
            return<\/p>\n
    messagebox.showerror("Login Failed", "Unknown user!")<\/p>\n
\u52a0\u8f7d\u5df2\u6ce8\u518c\u7528\u6237\u7684\u9762\u90e8\u7279\u5f81\u7f16\u7801<\/strong><\/h2>\n
registered_encodings = {<\/p>\n
    "user1": face_recognition.face_encodings(face_recognition.load_image_file("user1.jpg"))[0],<\/p>\n
    "user2": face_recognition.face_encodings(face_recognition.load_image_file("user2.jpg"))[0]<\/p>\n
}<\/p>\n
root = tk.Tk()<\/p>\n
root.title("Face Recognition Login")<\/p>\n
login_button = tk.Button(root, text="Login", command=login)<\/p>\n
login_button.pack()<\/p>\n
root.mainloop()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u63d0\u9ad8\u4eba\u8138\u8bc6\u522b\u7cfb\u7edf\u7684\u51c6\u786e\u6027\u548c\u5b89\u5168\u6027<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u63d0\u9ad8\u4eba\u8138\u8bc6\u522b\u7cfb\u7edf\u7684\u51c6\u786e\u6027\u548c\u5b89\u5168\u6027\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5efa\u8bae\uff1a<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528\u591a\u79cd\u6a21\u578b\u548c\u7b97\u6cd5<\/h4>\n<\/p>\n
\u7ed3\u5408\u591a\u79cd\u4eba\u8138\u68c0\u6d4b\u548c\u8bc6\u522b\u7b97\u6cd5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u7cfb\u7edf\u7684\u9c81\u68d2\u6027\u548c\u51c6\u786e\u6027\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u540c\u65f6\u4f7f\u7528OpenCV\u548cDlib\u7684\u68c0\u6d4b\u7ed3\u679c\uff0c\u5e76\u8fdb\u884c\u4ea4\u53c9\u9a8c\u8bc1\u3002<\/p>\n<\/p>\n
2\u3001\u6570\u636e\u589e\u5f3a\u548c\u9884\u5904\u7406<\/h4>\n<\/p>\n
\u901a\u8fc7\u6570\u636e\u589e\u5f3a\u6280\u672f\uff0c\u5982\u65cb\u8f6c\u3001\u7f29\u653e\u3001\u5e73\u79fb\u7b49\uff0c\u53ef\u4ee5\u589e\u52a0\u8bad\u7ec3\u6570\u636e\u7684\u591a\u6837\u6027\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002\u6b64\u5916\uff0c\u56fe\u50cf\u9884\u5904\u7406\uff08\u5982\u5f52\u4e00\u5316\u3001\u5747\u8861\u5316\uff09\u4e5f\u53ef\u4ee5\u63d0\u9ad8\u8bc6\u522b\u6548\u679c\u3002<\/p>\n<\/p>\n
3\u3001\u591a\u56e0\u7d20\u8ba4\u8bc1<\/h4>\n<\/p>\n
\u4e3a\u4e86\u63d0\u9ad8\u5b89\u5168\u6027\uff0c\u53ef\u4ee5\u5c06\u4eba\u8138\u8bc6\u522b\u4e0e\u5176\u4ed6\u8ba4\u8bc1\u65b9\u5f0f\uff08\u5982\u5bc6\u7801\u3001\u6307\u7eb9\uff09\u7ed3\u5408\uff0c\u5f62\u6210\u591a\u56e0\u7d20\u8ba4\u8bc1\u7cfb\u7edf\u3002\u8fd9\u6837\u53ef\u4ee5\u6709\u6548\u9632\u6b62\u5355\u4e00\u8ba4\u8bc1\u65b9\u5f0f\u7684\u6f0f\u6d1e\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u90e8\u7f72\u548c\u7ef4\u62a4<\/h3>\n<\/p>\n
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1\u3001\u672c\u5730\u90e8\u7f72<\/h4>\n<\/p>\n
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