Python在人脸识别技术中的前沿进展

pip install opencv-python
pip install dlib
pip install face_recognition

import cv2

# 加载人脸检测器
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# 加载图像
image = cv2.imread('image.jpg')

# 将图像转换为灰度图
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 检测人脸
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

# 绘制检测到的人脸
for (x, y, w, h) in faces:
    cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)

# 显示结果
cv2.imshow('Faces', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

import face_recognition

# 加载图像
image = face_recognition.load_image_file('image.jpg')

# 查找人脸特征
face_landmarks_list = face_recognition.face_landmarks(image)

# 绘制人脸特征
for face_landmarks in face_landmarks_list:
    for facial_feature in face_landmarks.keys():
        for pt in face_landmarks[facial_feature]:
            cv2.circle(image, pt, 2, (0, 255, 0), -1)

# 显示结果
cv2.imshow('Facial Landmarks', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

import face_recognition

# 加载已知人脸
known_face_encodings = [
    face_recognition.face_encodings(face_recognition.load_image_file('known_face1.jpg'))[0],
    face_recognition.face_encodings(face_recognition.load_image_file('known_face2.jpg'))[0],
    ...
]

# 加载未知人脸
unknown_image = face_recognition.load_image_file('unknown_face.jpg')

# 提取人脸特征
unknown_face_encodings = face_recognition.face_encodings(unknown_image)

# 比较人脸特征
for unknown_face_encoding in unknown_face_encodings:
    results = face_recognition.compare_faces(known_face_encodings, unknown_face_encoding)

    name = 'Unknown'
    if True in results:
        index = results.index(True)
        name = 'Known Face {}'.format(index + 1)

    print(name)