serengil/deepface

Health v2 · maintenance only

Adoption not part of the score

23340 stars · 3168 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DeepFace is a lightweight Python library for face recognition and facial attribute analysis, wrapping state-of-the-art models like VGG-Face, FaceNet, ArcFace, and DeepID behind a simple API. It also predicts age, gender, emotion, and race from face images and supports face detection, verification, and similarity search.

Use cases

• verify if two face photos belong to the same person
• find matching faces in a database of images
• predict age and gender from a face photo
• detect facial emotions like happy, sad, or angry
• build a face login or attendance system
• extract face embeddings for downstream ML tasks
• detect and align faces in images

When to choose

• you need face recognition in Python with a simple high-level API
• you want to compare multiple state-of-the-art face models without reimplementing them
• you need facial attribute analysis (age, gender, emotion, race) alongside recognition
• you want a lightweight, MIT-licensed alternative to cloud face APIs

When to avoid

• you need real-time recognition on edge devices with strict latency budgets
• you require training or fine-tuning face models from scratch
• you need non-face computer vision tasks
• your use case involves sensitive biometric data and you cannot accept the ethical/legal burden

Facets

library · maturity stable

machine-learning deep-learning computer-vision image-processing computer-vision image-processing artificial-intelligence deep-learning python cross-platform face-recognition facial-attribute-analysis age-prediction gender-prediction emotion-recognition race-classification facenet arcface vgg-face keras tensorflow

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