人脸搜索11.11活动

import face_recognition
import cv2
import numpy as np

# 加载已知人脸图像和对应的名称
known_image = face_recognition.load_image_file("known_person.jpg")
known_face_encoding = face_recognition.face_encodings(known_image)[0]
known_face_names = ["Known Person"]

# 初始化视频捕获
video_capture = cv2.VideoCapture(0)

while True:
    # 抓取一帧视频
    ret, frame = video_capture.read()

    # 将视频帧转换为RGB格式
    rgb_frame = frame[:, :, ::-1]

    # 查找当前帧中所有人脸的编码
    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    for face_encoding in face_encodings:
        # 比较当前人脸编码与已知人脸编码
        matches = face_recognition.compare_faces([known_face_encoding], face_encoding)
        name = "Unknown"

        if True in matches:
            first_match_index = matches.index(True)
            name = known_face_names[first_match_index]

        # 在帧上绘制人脸框和名称
        for (top, right, bottom, left) in face_locations:
            cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
            cv2.putText(frame, name, (left + 6, bottom - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)

    # 显示结果帧
    cv2.imshow('Video', frame)

    # 按q键退出循环
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 清理资源
video_capture.release()
cv2.destroyAllWindows()