Poor Man's Rekognition

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Google Summer Of Code Project under CCExtractor Development

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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.