deploy-docker-gesture-recognition

We aim to deploy gesture recognition model on docker with Flask. The model here is 3D Neural Network to correctly recognize hand gestures by a user.

Some terminlogies :

Docker container: Docker is like a container where the code is loaded so that it can be used on any platform without any dependency.
Docker Image: It's a read-only file that has multiple layers that help us to execute layers in docker containers. We can get a custom docker image.
Docker Hub: Different Docker Images resides here.

Benefits of docker:

• The development process is easy.
• Scalability.

Deploy ML model using Flask and Docker:

The steps followed to deploy the model using docker are:

1. Train and Evaluate the Model
2. Create an API using Flask
3. Create a requirements.txt file
4. Create a Dockerfile which has required environment setup and start-up operations.
5. Build the Docker Image
6. Run the container
7. Test the deployment

Dataset and Input to model:

The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds long) is divided into a sequence of 30 frames(images). These videos have been recorded by various people performing one of the five gestures in front of a webcam - similar to what the smart TV will use.
The videos have two types of dimensions - either 360x360 or 120x160 (depending on the webcam used to record the videos).

please refer the files commands.txt for step-wise instructions deployment on docker and Kubernetes