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serengil/deepface

📈 Trending★ 22,790PythonAudience · developerComplexity · 2/5ActiveLicenseSetup · moderate

TLDR

Python library for face recognition and facial attribute analysis. Identify who's in a photo and extract characteristics like age, emotion, and gender with a few lines of code.

Mindmap

mindmap
  root((DeepFace))
    What it does
      Face recognition
      Attribute analysis
      Face detection
    Key functions
      verify two faces
      find matches
      analyze attributes
    Use cases
      Security systems
      Photo organization
      Attendance tracking
    Tech stack
      Python
      Deep learning
      PostgreSQL
      MongoDB
    How it works
      Face detection
      Face alignment
      Embedding generation
      Similarity comparison

Things people build with this

USE CASE 1

Build a security system that verifies whether someone is who they claim to be by comparing their face to a stored photo.

USE CASE 2

Create a photo organization tool that automatically groups photos by the people in them.

USE CASE 3

Set up an attendance system that recognizes employees by their faces when they arrive at work.

USE CASE 4

Analyze a dataset of photos to extract age, emotion, and gender estimates for research or demographic analysis.

Tech stack

PythonDeep LearningPostgreSQLMongoDB

Getting it running

Difficulty · moderate Time to first run · 30min

Requires downloading pre-trained deep learning models on first use, which can be several hundred MB.

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

DeepFace is a Python library for face recognition and facial attribute analysis. Face recognition means automatically identifying who a person is by analyzing their face in a photo. Facial attribute analysis means extracting characteristics from a face, such as estimated age, apparent gender, emotional expression, and perceived ethnicity. The problem it solves: building a face recognition system from scratch requires deep expertise in computer vision and machine learning. DeepFace wraps several well-known AI models behind a simple Python interface, so you can get face recognition working with just a few lines of code. How it works: under the hood, the library runs a pipeline on each face image, detecting the face in the photo, aligning it to a standard position, and then generating a mathematical representation called an embedding. To compare two faces, it measures how similar their embeddings are. To analyze attributes, it runs separate models trained to estimate age, emotion, and other characteristics. All of this happens automatically when you call simple functions like verify (are these two photos the same person?), find (search a folder of photos for a match), or analyze (what attributes does this face have?). You would use DeepFace when building a system that needs to match or identify faces, security applications, photo organization tools, attendance systems, or research projects. The tech stack is Python, using deep learning models with optional database backends including PostgreSQL and MongoDB for large-scale search.

Copy-paste prompts

Prompt 1
Show me how to use DeepFace to verify if two photos contain the same person. I want a simple code example.
Prompt 2
How do I use DeepFace to search a folder of photos and find all images containing a specific person's face?
Prompt 3
Write a script using DeepFace that analyzes a photo and tells me the estimated age, gender, and emotion of each face in it.
Prompt 4
How do I set up DeepFace with PostgreSQL to store face embeddings and search a large database of photos efficiently?
Prompt 5
Can you show me how to use DeepFace's face detection and alignment features before passing faces to my own custom model?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.