{"id":1072175,"date":"2025-01-08T11:13:52","date_gmt":"2025-01-08T03:13:52","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1072175.html"},"modified":"2025-01-08T11:13:55","modified_gmt":"2025-01-08T03:13:55","slug":"%e5%a6%82%e4%bd%95%e5%86%99python%e6%a3%80%e6%b5%8b%e8%af%be%e5%a0%82%e6%8a%ac%e5%a4%b4%e7%8e%87-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1072175.html","title":{"rendered":"\u5982\u4f55\u5199python\u68c0\u6d4b\u8bfe\u5802\u62ac\u5934\u7387"},"content":{"rendered":"

\"\u5982\u4f55\u5199python\u68c0\u6d4b\u8bfe\u5802\u62ac\u5934\u7387\"<\/p>\n

\u8981\u5199Python\u68c0\u6d4b\u8bfe\u5802\u62ac\u5934\u7387\u7684\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u68c0\u6d4b\u9762\u90e8\u7279\u5f81\u3001\u5e94\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3001\u4f7f\u7528\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf\u3002<\/strong><\/p>\n<\/p>\n

\u5176\u4e2d\uff0c\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9<\/strong>\u662f\u6700\u5173\u952e\u7684\u4e00\u6b65\u3002\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u901a\u8fc7\u6444\u50cf\u5934\u83b7\u53d6\u8bfe\u5802\u5b9e\u65f6\u56fe\u50cf\uff0c\u5229\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u68c0\u6d4b\u5b66\u751f\u9762\u90e8\u4f4d\u7f6e\u548c\u59ff\u52bf\uff0c\u8ba1\u7b97\u51fa\u62ac\u5934\u7387\u3002\u4e0b\u9762\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u5229\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u6df1\u5ea6\u5b66\u4e60\u5b9e\u73b0\u8fd9\u4e00\u76ee\u6807\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f<\/h3>\n<\/p>\n

\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u662f\u901a\u8fc7\u6444\u50cf\u5934\u83b7\u53d6\u56fe\u50cf\uff0c\u7136\u540e\u5bf9\u8fd9\u4e9b\u56fe\u50cf\u8fdb\u884c\u5904\u7406\u548c\u5206\u6790\uff0c\u4ee5\u68c0\u6d4b\u548c\u8bc6\u522b\u7269\u4f53\u3001\u9762\u90e8\u3001\u59ff\u52bf\u7b49\u3002\u8981\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u5b9e\u73b0\u8bfe\u5802\u62ac\u5934\u7387\u68c0\u6d4b\uff0c\u9996\u5148\u9700\u8981\u6444\u50cf\u5934\u8bbe\u5907\u6765\u6355\u6349\u8bfe\u5802\u5b9e\u65f6\u89c6\u9891\u3002<\/p>\n<\/p>\n

1. \u89c6\u9891\u6355\u6349<\/h4>\n<\/p>\n

\u4f7f\u7528OpenCV\u5e93\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u89c6\u9891\u6355\u6349\u529f\u80fd\u3002\u5b89\u88c5OpenCV\u5e93\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b8c\u6210\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6355\u6349\u89c6\u9891\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u6253\u5f00\u6444\u50cf\u5934<\/strong><\/h2>\n
cap = cv2.VideoCapture(0)<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    if not ret:<\/p>\n
        break<\/p>\n
    # \u663e\u793a\u89c6\u9891\u5e27<\/p>\n
    cv2.imshow('Video', frame)<\/p>\n
    # \u6309\u4e0bq\u952e\u9000\u51fa<\/p>\n
    if cv2.wAI<\/a>tKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90<\/strong><\/h2>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u68c0\u6d4b\u9762\u90e8\u7279\u5f81<\/h3>\n<\/p>\n
\u5728\u6355\u6349\u5230\u89c6\u9891\u5e27\u540e\uff0c\u9700\u8981\u4f7f\u7528\u9762\u90e8\u68c0\u6d4b\u7b97\u6cd5\u6765\u8bc6\u522b\u5b66\u751f\u7684\u9762\u90e8\u7279\u5f81\u3002\u5e38\u7528\u7684\u9762\u90e8\u68c0\u6d4b\u7b97\u6cd5\u5305\u62ecHaar\u7ea7\u8054\u5206\u7c7b\u5668\u548cDlib\u5e93\u7684HOG+SVM\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
1. Haar\u7ea7\u8054\u5206\u7c7b\u5668<\/h4>\n<\/p>\n
Haar\u7ea7\u8054\u5206\u7c7b\u5668\u662f\u4e00\u79cd\u5feb\u901f\u6709\u6548\u7684\u9762\u90e8\u68c0\u6d4b\u65b9\u6cd5\u3002OpenCV\u63d0\u4f9b\u4e86\u9884\u8bad\u7ec3\u7684Haar\u7ea7\u8054\u5206\u7c7b\u5668\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u52a0\u8f7d\u9884\u8bad\u7ec3\u7684Haar\u7ea7\u8054\u5206\u7c7b\u5668<\/strong><\/h2>\n
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')<\/p>\n
\u6253\u5f00\u6444\u50cf\u5934<\/strong><\/h2>\n
cap = cv2.VideoCapture(0)<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    if not ret:<\/p>\n
        break<\/p>\n
    # \u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/p>\n
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)<\/p>\n
    # \u68c0\u6d4b\u9762\u90e8<\/p>\n
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))<\/p>\n
    # \u6807\u8bb0\u9762\u90e8<\/p>\n
    for (x, y, w, h) in faces:<\/p>\n
        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)<\/p>\n
    # \u663e\u793a\u89c6\u9891\u5e27<\/p>\n
    cv2.imshow('Video', frame)<\/p>\n
    # \u6309\u4e0bq\u952e\u9000\u51fa<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90<\/strong><\/h2>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. Dlib\u5e93\u7684HOG+SVM\u65b9\u6cd5<\/h4>\n<\/p>\n
Dlib\u5e93\u63d0\u4f9b\u4e86\u53e6\u4e00\u79cd\u9ad8\u6548\u7684\u9762\u90e8\u68c0\u6d4b\u65b9\u6cd5\u3002\u5b89\u88c5Dlib\u5e93\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b8c\u6210\uff1a<\/p>\n<\/p>\n
pip install dlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8fdb\u884c\u9762\u90e8\u68c0\u6d4b\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import dlib<\/p>\n
\u52a0\u8f7dDlib\u7684HOG+SVM\u9762\u90e8\u68c0\u6d4b\u5668<\/strong><\/h2>\n
detector = dlib.get_frontal_face_detector()<\/p>\n
\u6253\u5f00\u6444\u50cf\u5934<\/strong><\/h2>\n
cap = cv2.VideoCapture(0)<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    if not ret:<\/p>\n
        break<\/p>\n
    # \u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/p>\n
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)<\/p>\n
    # \u68c0\u6d4b\u9762\u90e8<\/p>\n
    faces = detector(gray)<\/p>\n
    # \u6807\u8bb0\u9762\u90e8<\/p>\n
    for face in faces:<\/p>\n
        x, y, w, h = (face.left(), face.top(), face.width(), face.height())<\/p>\n
        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)<\/p>\n
    # \u663e\u793a\u89c6\u9891\u5e27<\/p>\n
    cv2.imshow('Video', frame)<\/p>\n
    # \u6309\u4e0bq\u952e\u9000\u51fa<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90<\/strong><\/h2>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5e94\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b<\/h3>\n<\/p>\n
\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5728\u9762\u90e8\u7279\u5f81\u68c0\u6d4b\u548c\u59ff\u52bf\u8bc6\u522b\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002\u5e38\u7528\u7684\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5305\u62ecMTCNN\u3001FaceNet\u3001OpenPose\u7b49\u3002\u4e0b\u9762\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528MTCNN\u8fdb\u884c\u9762\u90e8\u68c0\u6d4b\u548c\u59ff\u52bf\u8bc6\u522b\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5MTCNN\u5e93<\/h4>\n<\/p>\n
\u5b89\u88c5MTCNN\u5e93\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b8c\u6210\uff1a<\/p>\n<\/p>\n
pip install mtcnn<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u4f7f\u7528MTCNN\u8fdb\u884c\u9762\u90e8\u68c0\u6d4b<\/h4>\n<\/p>\n
\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528MTCNN\u8fdb\u884c\u9762\u90e8\u68c0\u6d4b\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
from mtcnn.mtcnn import MTCNN<\/p>\n
\u52a0\u8f7dMTCNN\u9762\u90e8\u68c0\u6d4b\u5668<\/strong><\/h2>\n
detector = MTCNN()<\/p>\n
\u6253\u5f00\u6444\u50cf\u5934<\/strong><\/h2>\n
cap = cv2.VideoCapture(0)<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    if not ret:<\/p>\n
        break<\/p>\n
    # \u68c0\u6d4b\u9762\u90e8<\/p>\n
    results = detector.detect_faces(frame)<\/p>\n
    # \u6807\u8bb0\u9762\u90e8<\/p>\n
    for result in results:<\/p>\n
        x, y, w, h = result['box']<\/p>\n
        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)<\/p>\n
    # \u663e\u793a\u89c6\u9891\u5e27<\/p>\n
    cv2.imshow('Video', frame)<\/p>\n
    # \u6309\u4e0bq\u952e\u9000\u51fa<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90<\/strong><\/h2>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf<\/h3>\n<\/p>\n
\u4e3a\u4e86\u5b9e\u73b0\u5b9e\u65f6\u76d1\u63a7\u8bfe\u5802\u62ac\u5934\u7387\uff0c\u9700\u8981\u5bf9\u89c6\u9891\u5e27\u8fdb\u884c\u5b9e\u65f6\u5904\u7406\uff0c\u5e76\u8ba1\u7b97\u6bcf\u4e2a\u5b66\u751f\u7684\u62ac\u5934\u7387\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n
1. \u8ba1\u7b97\u62ac\u5934\u7387<\/h4>\n<\/p>\n
\u62ac\u5934\u7387\u662f\u6307\u5b66\u751f\u5728\u6307\u5b9a\u65f6\u95f4\u6bb5\u5185\u62ac\u5934\u7684\u9891\u7387\u3002\u53ef\u4ee5\u901a\u8fc7\u68c0\u6d4b\u9762\u90e8\u4f4d\u7f6e\u548c\u59ff\u52bf\u53d8\u5316\u6765\u8ba1\u7b97\u62ac\u5934\u7387\u3002\u4ee5\u4e0b\u662f\u8ba1\u7b97\u62ac\u5934\u7387\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
from mtcnn.mtcnn import MTCNN<\/p>\n
import time<\/p>\n
\u52a0\u8f7dMTCNN\u9762\u90e8\u68c0\u6d4b\u5668<\/strong><\/h2>\n
detector = MTCNN()<\/p>\n
\u6253\u5f00\u6444\u50cf\u5934<\/strong><\/h2>\n
cap = cv2.VideoCapture(0)<\/p>\n
\u521d\u59cb\u5316\u62ac\u5934\u8ba1\u6570\u5668<\/strong><\/h2>\n
head_up_count = 0<\/p>\n
total_frames = 0<\/p>\n
start_time = time.time()<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    if not ret:<\/p>\n
        break<\/p>\n
    # \u68c0\u6d4b\u9762\u90e8<\/p>\n
    results = detector.detect_faces(frame)<\/p>\n
    # \u6807\u8bb0\u9762\u90e8\u5e76\u8ba1\u7b97\u62ac\u5934\u7387<\/p>\n
    for result in results:<\/p>\n
        x, y, w, h = result['box']<\/p>\n
        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)<\/p>\n
        # \u8ba1\u7b97\u62ac\u5934\u7387<\/p>\n
        if y < frame.shape[0] \/ 2:<\/p>\n
            head_up_count += 1<\/p>\n
    total_frames += 1<\/p>\n
    # \u663e\u793a\u89c6\u9891\u5e27<\/p>\n
    cv2.imshow('Video', frame)<\/p>\n
    # \u6309\u4e0bq\u952e\u9000\u51fa<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
\u8ba1\u7b97\u62ac\u5934\u7387<\/strong><\/h2>\n
end_time = time.time()<\/p>\n
duration = end_time - start_time<\/p>\n
head_up_rate = head_up_count \/ total_frames<\/p>\n
print(f'\u62ac\u5934\u7387: {head_up_rate:.2f}')<\/p>\n
print(f'\u603b\u65f6\u95f4: {duration:.2f}\u79d2')<\/p>\n
\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90<\/strong><\/h2>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4f7f\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\u3001\u68c0\u6d4b\u9762\u90e8\u7279\u5f81\u3001\u5e94\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u548c\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u5b9e\u73b0\u8bfe\u5802\u62ac\u5934\u7387\u7684\u68c0\u6d4b\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e0d\u4ec5\u80fd\u591f\u63d0\u9ad8\u8bfe\u5802\u7ba1\u7406\u6548\u7387\uff0c\u8fd8\u80fd\u5e2e\u52a9\u6559\u5e08\u66f4\u597d\u5730\u4e86\u89e3\u5b66\u751f\u7684\u5b66\u4e60\u72b6\u6001\u548c\u53c2\u4e0e\u5ea6\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5229\u7528Python\u6536\u96c6\u8bfe\u5802\u62ac\u5934\u7387\u7684\u6570\u636e\uff1f<\/strong>
\u8981\u6536\u96c6\u8bfe\u5802\u62ac\u5934\u7387\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u4f8b\u5982OpenCV\u6216dlib\u3002\u901a\u8fc7\u8bbe\u7f6e\u4e00\u4e2a\u6444\u50cf\u5934\u6765\u6355\u6349\u5b66\u751f\u7684\u9762\u90e8\u8868\u60c5\uff0c\u8bc6\u522b\u4ed6\u4eec\u7684\u89c6\u7ebf\u65b9\u5411\uff0c\u4ece\u800c\u5224\u65ad\u4ed6\u4eec\u662f\u5426\u5728\u5173\u6ce8\u8bfe\u5802\u3002\u53ef\u4ee5\u901a\u8fc7\u7f16\u5199\u4ee3\u7801\u6765\u5206\u6790\u6bcf\u4e2a\u5b66\u751f\u7684\u9762\u90e8\u56fe\u50cf\uff0c\u7edf\u8ba1\u62ac\u5934\u7684\u9891\u7387\u3002<\/p>\n
\u5728\u8bfe\u5802\u4e0a\u4f7f\u7528Python\u68c0\u6d4b\u62ac\u5934\u7387\u7684\u6280\u672f\u8981\u6c42\u662f\u4ec0\u4e48\uff1f<\/strong>
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