{"id":1105456,"date":"2025-01-08T16:31:06","date_gmt":"2025-01-08T08:31:06","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1105456.html"},"modified":"2025-01-08T16:31:09","modified_gmt":"2025-01-08T08:31:09","slug":"python%e5%a6%82%e4%bd%95%e5%81%9a%e6%91%84%e5%83%8f%e5%a4%b4%e8%87%aa%e5%8a%a8%e8%b7%9f%e8%b8%aa","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1105456.html","title":{"rendered":"python\u5982\u4f55\u505a\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a"},"content":{"rendered":"

\"python\u5982\u4f55\u505a\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\"<\/p>\n

Python\u505a\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\u7684\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528OpenCV\u5e93\u8fdb\u884c\u5bf9\u8c61\u68c0\u6d4b\u3001\u7ed3\u5408\u8ddf\u8e2a\u7b97\u6cd5\u3001\u63a7\u5236\u6444\u50cf\u5934\u5b9e\u73b0\u81ea\u52a8\u8ddf\u8e2a\u3002<\/strong> \u5176\u4e2d\uff0c\u4f7f\u7528OpenCV\u5e93\u8fdb\u884c\u5bf9\u8c61\u68c0\u6d4b\u662f\u6700\u5e38\u7528\u7684\u65b9\u6cd5\uff0c\u901a\u8fc7\u7ed3\u5408\u8ddf\u8e2a\u7b97\u6cd5\uff0c\u53ef\u4ee5\u5b9e\u73b0\u5bf9\u5bf9\u8c61\u7684\u6301\u7eed\u8ddf\u8e2a\uff0c\u5e76\u901a\u8fc7\u63a7\u5236\u6444\u50cf\u5934\u7684\u8fd0\u52a8\uff0c\u4f7f\u5176\u59cb\u7ec8\u4fdd\u6301\u5bf9\u76ee\u6807\u5bf9\u8c61\u7684\u5173\u6ce8\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u5b9e\u73b0\u6444\u50cf\u5934\u7684\u81ea\u52a8\u8ddf\u8e2a\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u4f7f\u7528OpenCV\u8fdb\u884c\u5bf9\u8c61\u68c0\u6d4b<\/h3>\n<\/p>\n

1\u3001\u5b89\u88c5OpenCV\u5e93<\/h4>\n<\/p>\n

\u8981\u4f7f\u7528OpenCV\u8fdb\u884c\u5bf9\u8c61\u68c0\u6d4b\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5OpenCV\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u52a0\u8f7d\u6444\u50cf\u5934<\/h4>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u52a0\u8f7d\u6444\u50cf\u5934\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
cap = cv2.VideoCapture(0)  # 0\u8868\u793a\u7b2c\u4e00\u4e2a\u6444\u50cf\u5934<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5bf9\u8c61\u68c0\u6d4b<\/h4>\n<\/p>\n
\u5728\u8fdb\u884c\u5bf9\u8c61\u68c0\u6d4b\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u9884\u8bad\u7ec3\u7684Haar\u7ea7\u8054\u5206\u7c7b\u5668\u8fdb\u884c\u4eba\u8138\u68c0\u6d4b\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)<\/p>\n
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)<\/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
    cv2.imshow('Frame', frame)<\/p>\n
    if cv2.wAI<\/a>tKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u7ed3\u5408\u8ddf\u8e2a\u7b97\u6cd5<\/h3>\n<\/p>\n
1\u3001\u9009\u62e9\u8ddf\u8e2a\u7b97\u6cd5<\/h4>\n<\/p>\n
OpenCV\u63d0\u4f9b\u4e86\u591a\u79cd\u8ddf\u8e2a\u7b97\u6cd5\uff0c\u5305\u62ecKCF\u3001MIL\u3001CSRT\u7b49\u3002\u8fd9\u91cc\u4ee5KCF\uff08Kernelized Correlation Filters\uff09\u8ddf\u8e2a\u7b97\u6cd5\u4e3a\u4f8b\uff0c\u8fdb\u884c\u4ecb\u7ecd\u3002<\/p>\n<\/p>\n
2\u3001\u521d\u59cb\u5316\u8ddf\u8e2a\u5668<\/h4>\n<\/p>\n
\u5728\u5bf9\u8c61\u68c0\u6d4b\u540e\uff0c\u53ef\u4ee5\u9009\u62e9\u4e00\u4e2a\u5bf9\u8c61\u8fdb\u884c\u8ddf\u8e2a\uff0c\u5e76\u521d\u59cb\u5316\u8ddf\u8e2a\u5668\uff1a<\/p>\n<\/p>\n
tracker = cv2.TrackerKCF_create()<\/p>\n
ret, frame = cap.read()<\/p>\n
bbox = cv2.selectROI(frame, False)<\/p>\n
tracker.init(frame, bbox)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u66f4\u65b0\u8ddf\u8e2a\u5668<\/h4>\n<\/p>\n
\u5728\u89c6\u9891\u6d41\u4e2d\uff0c\u4e0d\u65ad\u66f4\u65b0\u8ddf\u8e2a\u5668\u7684\u4f4d\u7f6e\uff0c\u5e76\u5728\u5e27\u4e2d\u7ed8\u5236\u51fa\u8ddf\u8e2a\u6846\uff1a<\/p>\n<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    success, bbox = tracker.update(frame)<\/p>\n
    if success:<\/p>\n
        (x, y, w, h) = [int(v) for v in bbox]<\/p>\n
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)<\/p>\n
    else:<\/p>\n
        cv2.putText(frame, 'Tracking failure detected', (100, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)<\/p>\n
    cv2.imshow('Tracking', frame)<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u63a7\u5236\u6444\u50cf\u5934\u5b9e\u73b0\u81ea\u52a8\u8ddf\u8e2a<\/h3>\n<\/p>\n
1\u3001\u83b7\u53d6\u6444\u50cf\u5934\u7684\u63a7\u5236\u6743\u9650<\/h4>\n<\/p>\n
\u5bf9\u4e8ePTZ\uff08Pan-Tilt-Zoom\uff09\u6444\u50cf\u5934\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbf\u95ee\u6444\u50cf\u5934\u7684API\u6765\u63a7\u5236\u5176\u8fd0\u52a8\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5047\u8bbe\u4f60\u6709\u4e00\u4e2a\u652f\u6301HTTP\u63a7\u5236\u7684\u6444\u50cf\u5934\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
def move_camera(direction):<\/p>\n
    url = f'http:\/\/camera_ip\/command={direction}'<\/p>\n
    response = requests.get(url)<\/p>\n
    return response.status_code<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8ba1\u7b97\u6444\u50cf\u5934\u8fd0\u52a8\u65b9\u5411<\/h4>\n<\/p>\n
\u5728\u8ddf\u8e2a\u8fc7\u7a0b\u4e2d\uff0c\u6839\u636e\u8ddf\u8e2a\u6846\u7684\u4f4d\u7f6e\uff0c\u8ba1\u7b97\u6444\u50cf\u5934\u9700\u8981\u79fb\u52a8\u7684\u65b9\u5411\u3002\u6bd4\u5982\uff0c\u5982\u679c\u5bf9\u8c61\u5728\u5e27\u7684\u5de6\u4fa7\uff0c\u5219\u6444\u50cf\u5934\u9700\u8981\u5411\u5de6\u79fb\u52a8\uff1b\u5982\u679c\u5bf9\u8c61\u5728\u5e27\u7684\u53f3\u4fa7\uff0c\u5219\u6444\u50cf\u5934\u9700\u8981\u5411\u53f3\u79fb\u52a8\uff1a<\/p>\n<\/p>\n
frame_center = (frame.shape[1] \/\/ 2, frame.shape[0] \/\/ 2)<\/p>\n
object_center = (x + w \/\/ 2, y + h \/\/ 2)<\/p>\n
if object_center[0] < frame_center[0]:<\/p>\n
    move_camera('left')<\/p>\n
elif object_center[0] > frame_center[0]:<\/p>\n
    move_camera('right')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u7efc\u5408\u793a\u4f8b<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7efc\u5408\u7684\u793a\u4f8b\uff0c\u7ed3\u5408\u4e86\u5bf9\u8c61\u68c0\u6d4b\u3001\u8ddf\u8e2a\u7b97\u6cd5\u548c\u6444\u50cf\u5934\u63a7\u5236\uff0c\u5b9e\u73b0\u81ea\u52a8\u8ddf\u8e2a\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import requests<\/p>\n
cap = cv2.VideoCapture(0)<\/p>\n
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')<\/p>\n
tracker = cv2.TrackerKCF_create()<\/p>\n
def move_camera(direction):<\/p>\n
    url = f'http:\/\/camera_ip\/command={direction}'<\/p>\n
    response = requests.get(url)<\/p>\n
    return response.status_code<\/p>\n
while True:<\/p>\n
    ret, frame = cap.read()<\/p>\n
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)<\/p>\n
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)<\/p>\n
    if len(faces) > 0:<\/p>\n
        (x, y, w, h) = faces[0]<\/p>\n
        tracker.init(frame, (x, y, w, h))<\/p>\n
    success, bbox = tracker.update(frame)<\/p>\n
    if success:<\/p>\n
        (x, y, w, h) = [int(v) for v in bbox]<\/p>\n
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)<\/p>\n
        frame_center = (frame.shape[1] \/\/ 2, frame.shape[0] \/\/ 2)<\/p>\n
        object_center = (x + w \/\/ 2, y + h \/\/ 2)<\/p>\n
        if object_center[0] < frame_center[0]:<\/p>\n
            move_camera('left')<\/p>\n
        elif object_center[0] > frame_center[0]:<\/p>\n
            move_camera('right')<\/p>\n
    else:<\/p>\n
        cv2.putText(frame, 'Tracking failure detected', (100, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)<\/p>\n
    cv2.imshow('Tracking', frame)<\/p>\n
    if cv2.waitKey(1) & 0xFF == ord('q'):<\/p>\n
        break<\/p>\n
cap.release()<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0a\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528Python\u7ed3\u5408OpenCV\u5e93\u8fdb\u884c\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\uff0c\u5305\u62ec\u5bf9\u8c61\u68c0\u6d4b\u3001\u8ddf\u8e2a\u7b97\u6cd5\u548c\u6444\u50cf\u5934\u63a7\u5236\u3002\u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u53ef\u4ee5\u5b9e\u73b0\u5bf9\u76ee\u6807\u5bf9\u8c61\u7684\u6301\u7eed\u8ddf\u8e2a\u548c\u6444\u50cf\u5934\u7684\u81ea\u52a8\u8c03\u6574\uff0c\u4ee5\u4fdd\u6301\u5bf9\u76ee\u6807\u5bf9\u8c61\u7684\u5173\u6ce8\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5728Python\u4e2d\u5b9e\u73b0\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
\u8981\u5b9e\u73b0\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\uff0c\u9996\u5148\u9700\u8981\u9009\u62e9\u5408\u9002\u7684\u5e93\uff0c\u4f8b\u5982OpenCV\u3002\u63a5\u4e0b\u6765\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u8fdb\u884c\u64cd\u4f5c\uff1a  <\/p>\n
    \n
  1. \u5b89\u88c5OpenCV\u5e93\uff0c\u786e\u4fdd\u6444\u50cf\u5934\u6b63\u5e38\u5de5\u4f5c\u3002  <\/li>\n
  2. \u4f7f\u7528cv2.VideoCapture()\u51fd\u6570\u6355\u6349\u89c6\u9891\u6d41\u3002  <\/li>\n
  3. \u901a\u8fc7\u56fe\u50cf\u5904\u7406\u6280\u672f\uff08\u5982\u80cc\u666f\u51cf\u9664\u3001\u8fb9\u7f18\u68c0\u6d4b\u7b49\uff09\u68c0\u6d4b\u79fb\u52a8\u7684\u5bf9\u8c61\u3002  <\/li>\n
  4. \u4f7f\u7528\u7269\u4f53\u68c0\u6d4b\u7b97\u6cd5\uff08\u5982Haar\u7ea7\u8054\u5206\u7c7b\u5668\u6216YOLO\uff09\u8bc6\u522b\u76ee\u6807\u3002  <\/li>\n
  5. \u5229\u7528\u76ee\u6807\u7684\u4f4d\u7f6e\u4fe1\u606f\u8c03\u6574\u6444\u50cf\u5934\u7684\u89d2\u5ea6\u6216\u4f4d\u7f6e\u4ee5\u5b9e\u73b0\u8ddf\u8e2a\u3002<\/li>\n<\/ol>\n
    \u6709\u54ea\u4e9b\u5e38\u89c1\u7684\u7269\u4f53\u68c0\u6d4b\u7b97\u6cd5\u9002\u7528\u4e8e\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\uff1f<\/strong>
    \u5728\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\u4e2d\uff0c\u5e38\u7528\u7684\u7269\u4f53\u68c0\u6d4b\u7b97\u6cd5\u5305\u62ec\uff1a  <\/p>\n
      \n
    • Haar\u7ea7\u8054\u5206\u7c7b\u5668\uff1a\u9002\u5408\u4e8e\u4eba\u8138\u68c0\u6d4b\u548c\u7b80\u5355\u7269\u4f53\u7684\u8ddf\u8e2a\u3002  <\/li>\n
    • YOLO\uff08You Only Look Once\uff09\uff1a\u4e00\u79cd\u5b9e\u65f6\u7269\u4f53\u68c0\u6d4b\u7cfb\u7edf\uff0c\u80fd\u591f\u5feb\u901f\u8bc6\u522b\u591a\u4e2a\u7269\u4f53\u3002  <\/li>\n
    • SSD\uff08Single Shot MultiBox Detector\uff09\uff1a\u4e0eYOLO\u7c7b\u4f3c\uff0c\u80fd\u5728\u4e00\u4e2a\u524d\u5411\u4f20\u64ad\u4e2d\u68c0\u6d4b\u591a\u4e2a\u7269\u4f53\u3002  <\/li>\n
    • \u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\uff08\u5982Faster R-CNN\uff09\uff1a\u9002\u5408\u4e8e\u590d\u6742\u573a\u666f\u7684\u9ad8\u7cbe\u5ea6\u68c0\u6d4b\u3002
      \u8fd9\u4e9b\u7b97\u6cd5\u5404\u6709\u4f18\u7f3a\u70b9\uff0c\u9009\u62e9\u65f6\u5e94\u8003\u8651\u5e94\u7528\u573a\u666f\u548c\u8ba1\u7b97\u8d44\u6e90\u3002<\/li>\n<\/ul>\n
      \u5982\u4f55\u63d0\u5347\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\u7684\u51c6\u786e\u6027\u548c\u7a33\u5b9a\u6027\uff1f<\/strong>
      \u63d0\u5347\u6444\u50cf\u5934\u81ea\u52a8\u8ddf\u8e2a\u7684\u51c6\u786e\u6027\u548c\u7a33\u5b9a\u6027\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u6cd5\u5b9e\u73b0\uff1a  <\/p>\n
        \n
      • \u4f18\u5316\u7b97\u6cd5\u53c2\u6570\u8bbe\u7f6e\uff0c\u5982\u8c03\u6574\u9608\u503c\u548c\u6a21\u578b\u6743\u91cd\u3002  <\/li>\n
      • \u4f7f\u7528\u591a\u5e27\u56fe\u50cf\u878d\u5408\u6280\u672f\uff0c\u51cf\u5c11\u566a\u58f0\u5e72\u6270\u3002  <\/li>\n
      • \u7ed3\u5408\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\uff0c\u63d0\u5347\u68c0\u6d4b\u80fd\u529b\u3002  <\/li>\n
      • \u91c7\u7528\u4f20\u611f\u5668\u878d\u5408\u6280\u672f\uff0c\u4f8b\u5982\u7ed3\u5408IMU\uff08\u60ef\u6027\u6d4b\u91cf\u5355\u5143\uff09\u6570\u636e\uff0c\u63d0\u9ad8\u5b9a\u4f4d\u7cbe\u5ea6\u3002  <\/li>\n
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