Face Detection

retina face

Github - retinaface: deep learning based cutting-edge facial detector

deepface

Github - deepface: a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework

Install:

pip install deepface

Usage:

from deepface import DeepFace

# Detection: 从照片中检测人脸
face_objs = DeepFace.extract_faces(
    img_path = "img.jpg", 
    detector_backend = 'retinaface', # retina face 检测效果较好
    align = False,
    enforce_detection = False,
)

# Verification: 判断两张图片是否同一个人
result = DeepFace.verify(img1_path = "img1.jpg", img2_path = "img2.jpg")
# 默认会先做 detection，如果是已经提取了人脸的照片可以用
result = DeepFace.verify(img1_path = "img1.jpg", img2_path = "img2.jpg", detector_backend='skip')
# 指定相似度阈值
result = DeepFace.verify(img1_path = "img1.jpg", img2_path = "img2.jpg", threshold=0.5)

# Embedding: 提取人脸 embedding，可以用于后续的对比计算
embedding_objs = DeepFace.represent(img_path = "img.jpg")

# Recognition: 人脸识别，从人脸库中找出最符合的人
dfs = DeepFace.find(
    img_path = "img1.jpg",
    db_path = "./workspace/my_db", 
    model_name = "VGG-Face", # 默认模型是 VGG-Face
)

# Analysis：提取脸部特征（年龄、性别、情绪等）
objs = DeepFace.analyze(
    img_path = "img4.jpg", 
    actions = ['age', 'gender', 'race', 'emotion'],
)