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Rekognition

Free and Open Source alternative to Amazon's Rekognition service. CCExtractor Development | Poor Man's Rekognition

Install / Use

/learn @CCExtractor/Rekognition

README

Poor Man's Rekognition


Google Summer Of Code Project under CCExtractor Development

Build Status Python 3.X GPLv3 license


This project aims at providing a free alternative to Amazon Rekognition services.

Setup

For End-User

git clone https://github.com/pymit/Rekognition

docker image build ./

Note down the IMAGEID at the end and run the docker

docker run -p 8000:8000 <IMAGEID>

For Developers

To setup the project locally for development environment check this wiki link

Usage

This project currently supports | Feature | cURL | | :--- | :---- | Face Recognition with FaceNet |curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " --form network=1 http://127.0.0.1:8000/api/image/ | Face Recognition with RetinaNet |curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " --form network=2 http://127.0.0.1:8000/api/image/ | | Similar Face Search | curl -i -X POST -H "Content-Type: multipart/form-data" -F "file=@ <path to reference image>" -F "compareImage=@ <path to compare Image>" http://127.0.0.1:8000/api/simface/ | | NSFW Classifier | curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " http://127.0.0.1:8000/api/nsfw/ | | Text Extraction | curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " http://127.0.0.1:8000/api/scenetext/ | | Object Detection | curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " http://127.0.0.1:8000/api/objects/ | | Scene Classification | curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@<path to image file> " http://127.0.0.1:8000/api/scenedetect/ |

Details on documentation can be found here.

Communication

Real-time communication for this project happens on slack channel of CCExtractor Development, channel link. You may join this channel via this link

References

This project uses the following.

  1. FaceNet
  2. CRNN
  3. EAST
  4. Synth90k
  5. YOLOv3
  6. Places365
  7. RetinaFace

License

This software is licensed under GNU GPLv3. Please see the included License file.

Related Skills

View on GitHub
GitHub Stars117
CategoryDevelopment
Updated1mo ago
Forks56

Languages

Python

Security Score

100/100

Audited on Feb 13, 2026

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