Gather how to deploy tensorflow models as much I can
- Object Detection using Flask SocketIO for WebRTC
- Object Detection using Flask SocketIO for opencv
- Speech streaming using Flask SocketIO
- Classification using Flask + Gunicorn
- Classification using TF Serving
- Inception Classification using Flask SocketIO
- Object Detection using Flask + opencv
- Face-detection using Flask SocketIO for opencv
- Face-detection for opencv
- Inception with Flask using Docker
- Multiple Inception with Flask using EC2 Docker Swarm + Nginx load balancer
- Text classification using Hadoop streaming MapReduce
- Text classification using Kafka
- Text classification on Distributed TF using Flask + Gunicorn + Eventlet
- Text classification using Tornado + Gunicorn
- Celery with Hadoop for Massive text classification using Flask
- Luigi scheduler with Hadoop for Massive text classification
- Luigi scheduler with Distributed Celery for Massive text classification
- Airflow scheduler with elasticsearch for Massive text classification using Flask
- Flask SocketIO
- Luigi Spotify
- Elastic search
All folders contain print screens, logs and instructions on how to start.
- Deploy them on a server, change
localin code snippets to your own IP.
- WebRTC chrome only can tested on HTTPS server.
- When come to real deployment, always prepare for up-scaling architectures. Learn about DevOps.
- Please aware with your cloud cost!