face recognition service
CompreFace is a self-hosted face recognition system exposing REST APIs for detection, verification, recognition, landmark and attribute analysis, designed for easy Docker deployment.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose it when you need a lightweight Python library embedding current models directly in your code instead of deploying a REST service.
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Choose it when you need a bundled face SDK with liveness/anti-spoofing and templates and want to integrate at code level rather than through an HTTP API.
Face Recognition, Face Liveness Detection, Face Anti-Spoofing, Face Detection, Face Landmarks, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Templates Extraction, Face Landmarks
Choose it for the simplest Python face recognition API/CLI when you want direct in-process recognition without Docker/API overhead.
The world's simplest facial recognition api for Python and the command line
Choose it when you want a single Python API covering many face tasks (including recognition and parsing) without running a server.
UniFace: A Unified Face Analysis Library for Python | Detection, alignment, landmarks, face-mesh, recognition, parsing, gaze, attributes and anti-spoofing under one API.
Choose it for a modern JavaScript/browser face and body analysis library with recognition and pose, when you need no backend service.
Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition
Choose it for a PyTorch/Paddle face recognition research library when you need multiple benchmark model implementations in your own processing.
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Older but still used JS face recognition library for in-browser/Node projects; choose it if you accept an unmaintained offline solution.
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Classic Lua/Torch face recognition pipeline; choose it only if you are tied to that legacy framework and don't need a modern service.
Face recognition with deep neural networks.
These projects were analysed and named CompreFace among their alternatives. The relationship is not symmetric — how CompreFace rates them is a separate judgement, made when CompreFace is analysed in its own right.
calls CompreFace “Choose it when you want a Docker-deployed, language-agnostic face recognition service with REST/UI instead of an in-process JavaScript library.”
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
calls CompreFace “Choose for a self-hosted web/REST face-recognition system with UI instead of an in-process Python library.”
The world's simplest facial recognition api for Python and the command line
calls CompreFace “A ready-to-deploy face recognition system with GUI and REST API, ships as an end-user service.”
State-of-the-art 2D and 3D Face Analysis Project
calls CompreFace “when you need a self-hosted face-recognition system with a REST API and UI instead of a code-level library.”
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
calls CompreFace “choose when you want to deploy a self-hosted Docker face-recognition REST service rather than embed a Python model.”
Face recognition using Tensorflow