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https://github.com/exadel-inc/compreface
Leading free and open-source face recognition system
https://github.com/exadel-inc/compreface
computer-vision docker docker-compose face-detection face-identification face-mask-detection face-recognition face-verification facenet facial-recognition hacktoberfest hacktoberfest2021 insightface rest-api
Last synced: 7 days ago
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Leading free and open-source face recognition system
- Host: GitHub
- URL: https://github.com/exadel-inc/compreface
- Owner: exadel-inc
- License: apache-2.0
- Created: 2020-07-06T08:29:43.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-10-05T10:45:30.000Z (about 1 month ago)
- Last Synced: 2024-10-29T03:33:25.902Z (7 days ago)
- Topics: computer-vision, docker, docker-compose, face-detection, face-identification, face-mask-detection, face-recognition, face-verification, facenet, facial-recognition, hacktoberfest, hacktoberfest2021, insightface, rest-api
- Language: Java
- Homepage: https://exadel.com/accelerator-showcase/compreface/
- Size: 540 MB
- Stars: 5,469
- Watchers: 84
- Forks: 750
- Open Issues: 204
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
Exadel CompreFace is a leading free and open-source face recognition system
Exadel CompreFace is a free and open-source face recognition service that can be easily integrated into any system without prior machine learning skills.
CompreFace provides REST API for face recognition, face verification, face detection, landmark detection, mask detection, head pose detection, age, and gender recognition and is easily deployed with docker.
Contributing
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Submit an Issue
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# Table Of Contents
* [Overview](#overview)
* [Screenshots](#screenshots)
* [Video tutorials](#videos)
* [News and updates](#news-and-updates)
* [Features](#features)
* [Functionalities](#functionalities)
* [Getting Started with CompreFace](#getting-started-with-compreface)
* [CompreFace SDKs](#compreface-sdks)
* [Documentation](/docs)
* [How to Use CompreFace](/docs/How-to-Use-CompreFace.md)
* [Face Services and Plugins](/docs/Face-services-and-plugins.md)
* [Rest API Description](/docs/Rest-API-description.md)
* [Postman documentation and collection](https://documenter.getpostman.com/view/17578263/UUxzAnde)
* [Face Recognition Similarity Threshold](/docs/Face-Recognition-Similarity-Threshold.md)
* [Configuration](/docs/Configuration.md)
* [Architecture and Scalability](/docs/Architecture-and-scalability.md)
* [Custom Builds](/docs/Custom-builds.md)
* [Face data migration](/docs/Face-data-migration.md)
* [User Roles System](/docs/User-Roles-System.md)
* [Face Mask Detection Plugin](/docs/Mask-detection-plugin.md)
* [Kubernetes configuration](https://github.com/exadel-inc/compreface-kubernetes)
* [Gathering Anonymous Statistics](/docs/Gathering-anonymous-statistics.md)
* [Installation Options](/docs/Installation-options.md)
* [Contributing](#contributing)
* [License info](#license-info)
# Overview
Exadel CompreFace is a free and open-source face recognition GitHub project.
Essentially, it is a docker-based application that can be used as a standalone server or deployed in the cloud.
You don’t need prior machine learning skills to set up and use CompreFace.
The system provides REST API for face recognition, face verification, face detection, landmark detection, mask detection, head pose detection, age, and gender recognition.
The solution also features a role management system that allows you to easily control who has access to your Face Recognition Services.
CompreFace is delivered as a docker-compose config and supports different models that work on CPU and GPU.
Our solution is based on state-of-the-art methods and libraries like FaceNet and InsightFace.
# Screenshots
More Screenshots
# Videos
More Videos
# News and updates
[Subscribe](https://info.exadel.com/en/compreface-news-and-updates) to CompreFace News and Updates to never miss new features and product improvements.
# Features
The system can accurately identify people even when it has only “seen” their photo once. Technology-wise, CompreFace has several advantages over similar free face recognition solutions. CompreFace:
- Supports both CPU and GPU and is easy to scale up
- Is open source and self-hosted, which gives you additional guarantees for data security
- Can be deployed either in the cloud or on premises
- Can be set up and used without machine learning expertise
- Uses FaceNet and InsightFace libraries, which use state-of-the-art face recognition methods
- Starts quickly with just one docker command
# Functionalities
- Supports many face recognition services:
- [face detection](/docs/Face-services-and-plugins.md#face-detection)
- [face recognition](/docs/Face-services-and-plugins.md#face-recognition)
- [face verification](/docs/Face-services-and-plugins.md#face-verification)
- [landmark detection plugin](/docs/Face-services-and-plugins.md#face-plugins)
- [age recognition plugin](/docs/Face-services-and-plugins.md#face-plugins)
- [gender recognition plugin](/docs/Face-services-and-plugins.md#face-plugins)
- [face mask detection plugin](/docs/Face-services-and-plugins.md#face-plugins)
- [head pose plugin](/docs/Face-services-and-plugins.md#face-plugins)
- Use the CompreFace UI panel for convenient user roles and access management
# Getting Started with CompreFace
### Requirements
1. Docker and Docker compose (or Docker Desktop)
2. CompreFace could be run on most modern computers with [x86 processor](https://en.wikipedia.org/wiki/X86) and [AVX support](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions).
To check AVX support on Linux run `lscpu | grep avx` command
### To get started (Linux, MacOS):
1. Install Docker and Docker Compose
2. Download the archive from our latest release: https://github.com/exadel-inc/CompreFace/releases
3. Unzip the archive
4. Open the terminal in this folder and run this command: `docker-compose up -d`
5. Open the service in your browser: http://localhost:8000/login
### To get started (Windows):
1. Install Docker Desktop
2. Download the archive from our latest release: https://github.com/exadel-inc/CompreFace/releases
3. Unzip the archive
4. Run Docker
5. Open Command prompt (write `cmd` in windows search bar)
6. Open folder where you extracted zip archive (Write `cd path_of_the_folder`, press enter).
7. Run command: `docker-compose up -d`
8. Open http://localhost:8000/login
### Getting started for contributors
Follow this [link](/dev)
# CompreFace SDKs
| SDK | Repository |
|------------|---------------------------------------------------------|
| JavaScript | https://github.com/exadel-inc/compreface-javascript-sdk |
| Python | https://github.com/exadel-inc/compreface-python-sdk |
| .NET | https://github.com/exadel-inc/compreface-net-sdk |
# Documentation
More documentation is available [here](/docs)
# Contributing
We want to improve our open-source face recognition solution, so your contributions are welcome and greatly appreciated.
* Just use CompreFace and [report](https://github.com/exadel-inc/CompreFace/issues) ideas and bugs on GitHub
* Share knowledge and experience via posting guides and articles, or just improve our [documentation](https://github.com/exadel-inc/CompreFace/tree/master/docs)
* Create [SDKs](https://github.com/topics/compreface-sdk) for favorite programming language, we will add it to our documentation
* Integrate CompreFace support to other platforms like [Home Assistant](https://www.home-assistant.io/) or [DreamFactory](https://www.dreamfactory.com/), we will add it to our documentation
* [Contribute](CONTRIBUTING.md) code
* Add [plugin](/docs/Face-services-and-plugins.md#face-plugins) to face services
* And last, but not least, you can just give a star to our free facial recognition system on GitHub
For more information, visit our [contributing](CONTRIBUTING.md) guide, or create a [discussion](https://github.com/exadel-inc/CompreFace/discussions).
# License info
CompreFace is open-source real-time facial recognition software released under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.html).