Gather-Tensorflow-Serving

Gather how to deploy tensorflow models as much I can

Covered

1. Object Detection. Flask SocketIO + WebRTC
2. Object Detection. Flask SocketIO + opencv
3. Speech streaming. Flask SocketIO
4. Text classification. Flask + Gunicorn
5. Image classification. TF Serving
6. Image Classification using Inception. Flask SocketIO
7. Object Detection. Flask + opencv
8. Face-detection using MTCNN. Flask SocketIO + opencv
9. Face-detection using MTCNN. opencv
10. Image classification using Inception. Flask + Docker
11. Image classification using Inception. Flask + EC2 Docker Swarm + Nginx load balancer
12. Text classification. Hadoop streaming MapReduce
13. Text classification. Kafka
14. Text classification. Distributed TF using Flask + Gunicorn + Eventlet
15. Text classification. Tornado + Gunicorn
16. Text classification. Flask + Celery + Hadoop
17. Text classification. Luigi scheduler + Hadoop
18. Text classification. Luigi scheduler + Distributed Celery
19. Text classification. Airflow scheduler + elasticsearch + Flask
20. Text classification. Apache Kafka + Apache Storm

Technology used

1. Flask
2. Flask SocketIO
3. Gunicorn
4. Eventlet
5. Tornado
6. Celery
7. Hadoop
8. Kafka
9. Nginx
10. WebRTC
11. Luigi Spotify
12. Airflow
13. Elastic search
14. Apache Storm

Printscreen

All folders contain print screens, logs and instructions on how to start.

Notes

1. Deploy them on a server, change local in code snippets to your own IP.
2. WebRTC chrome only can tested on HTTPS server.
3. When come to real deployment, always prepare for up-scaling architectures. Learn about DevOps.
4. Please aware with your cloud cost!