摘要：pythonimport face_recognition# 加载已知人脸known_image = face_recognition.load_image_file("known.jpg")known_encoding = face_recognition.
项目名称: Face Recognition
Github: https://github.com/ageitgey/face_recognition
特点:
pythonimport face_recognition# 加载已知人脸known_image = face_recognition.load_image_file("known.jpg")known_encoding = face_recognition.face_encodings(known_image)[0]# 摄像头实时识别video_capture = cv2.VideoCapture(0)while True:ret, frame = video_capture.readface_locations = face_recognition.face_locations(frame)face_encodings = face_recognition.face_encodings(frame, face_locations)for face_encoding in face_encodings:matches = face_recognition.compare_faces([known_encoding], face_encoding)name = "Unknown"if True in matches:name = "Known Person"# 绘制识别结果...项目名称: InsightFace
Github: https://github.com/deepinsight/insightface
特点:
基于MXNet/PyTorch实现支持ArcFace等先进算法提供预训练模型支持大规模人脸识别
核心功能:pythonfrom insightface.app import FaceAnalysisapp = FaceAnalysis(name='buffalo_l')app.prepare(ctx_id=0, det_size=(640, 640))# 人脸特征提取faces = app.get(img)for face in faces:print(face.embedding) # 512维特征向量项目名称: FaceID
Github: https://github.com/pudae/tensorflow-faceid
技术栈:
项目名称: MobileFaceNet
论文: https://arxiv.org/abs/1804.07573
实现参考:
项目名称: Anti-Spoofing
Github: https://github.com/minivision-ai/Silent-Face-Anti-Spoofing
检测手段:
基础架构mermaidgraph TDA[摄像头] --> B(人脸检测)B --> C{是否活体?}C -->|Yes| D[特征提取]C -->|No| E[拒绝]D --> F[特征比对]F --> G[识别结果]关键技术点人脸对齐: 使用相似变换统一人脸角度特征降维: PCA处理从512维到128维相似度计算: 余弦相似度 + 阈值过滤pythondef cosine_similarity(a, b):return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))性能优化使用TensorRT加速推理部署Redis缓存特征向量多线程处理视频流 来源：小陈看科技
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