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https://github.com/ccextractor/rekognition
Free and Open Source alternative to Amazon's Rekognition service. CCExtractor Development | Poor Man's Rekognition
https://github.com/ccextractor/rekognition
computer-vision deep-learning django django-rest-framework docker face-detection gsoc image-processing machine-learning machinelearning opencv python rest rest-api tensorflow tensorflow-serving video-processing
Last synced: 22 days ago
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Free and Open Source alternative to Amazon's Rekognition service. CCExtractor Development | Poor Man's Rekognition
- Host: GitHub
- URL: https://github.com/ccextractor/rekognition
- Owner: CCExtractor
- License: gpl-3.0
- Created: 2019-05-18T02:04:07.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-03-08T12:22:47.000Z (almost 2 years ago)
- Last Synced: 2024-12-12T03:21:06.498Z (about 1 month ago)
- Topics: computer-vision, deep-learning, django, django-rest-framework, docker, face-detection, gsoc, image-processing, machine-learning, machinelearning, opencv, python, rest, rest-api, tensorflow, tensorflow-serving, video-processing
- Language: Python
- Homepage:
- Size: 3.23 MB
- Stars: 103
- Watchers: 8
- Forks: 53
- Open Issues: 24
-
Metadata Files:
- Readme: README.md
- Contributing: contributing.md
- License: LICENSE
Awesome Lists containing this project
README
## Poor Man's Rekognition
---
Google Summer Of Code Project under CCExtractor Development
[](https://travis-ci.org/CCExtractor/Rekognition)
[](https://www.python.org/downloads/)
[](https://github.com/ccextractor/Rekognition/blob/master/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
```
### For Developers
To setup the project locally for development environment check this wiki [link](https://github.com/YB221/Rekognition/blob/master/contributing.md)
## Usage
This project currently supports
| Feature | cURL |
| :--- | :---- |
Face Recognition with FaceNet |`curl -i -X POST -H "Content-Type: multipart/form-data " -F "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=@ " --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=@ " -F "compareImage=@ " http://127.0.0.1:8000/api/simface/` |
| NSFW Classifier | `curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@ " http://127.0.0.1:8000/api/nsfw/` |
| Text Extraction | `curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@ " http://127.0.0.1:8000/api/scenetext/` |
| Object Detection | `curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@ " http://127.0.0.1:8000/api/objects/` |
| Scene Classification | `curl -i -X POST -H "Content-Type: multipart/form-data " -F "file=@ " http://127.0.0.1:8000/api/scenedetect/` |
Details on documentation can be found [here](https://github.com/pymit/Rekognition/wiki/API-Documentation).
## Communication
Real-time communication for this project happens on slack channel of CCExtractor Development, channel [link](https://rhccgsoc15.slack.com/). You may join this channel via this [link](https://ccextractor.org/public:general:support)
## References
This project uses the following.
1. [FaceNet](https://github.com/davidsandberg/facenet)
2. [CRNN](https://arxiv.org/pdf/1507.05717.pdf)
3. [EAST](https://arxiv.org/pdf/1704.03155.pdf)
4. [Synth90k](https://www.robots.ox.ac.uk/~vgg/data/text/)
5. [YOLOv3](https://pjreddie.com/darknet/yolo/)
6. [Places365](http://places2.csail.mit.edu/)
7. [RetinaFace](https://arxiv.org/pdf/1905.00641.pdf)
## License
This software is licensed under GNU GPLv3. Please see the included [License file](https://github.com/pymit/Rekognition/blob/master/LICENSE).