laramaktub/image-classification-tf repository overview

⁠DEEP as a Service container for image classification

This is a container that will run the DEEP as a Service API component. From the DEEPaas API the user can choose the model to train or to predict, together with the basic input parameters.

⁠Run the container

⁠Directly from Docker Hub

To run the Docker container directly from Docker Hub and start using the API simply run the following command:

$ docker run -ti -p 5000:5000 -p 6006:6006 deephdc/deep-oc-image-classification-tf

This command will pull the Docker container from the Docker Hub deephdc⁠ organization.

⁠Building the container

If you want to build the container directly in your machine (because you want to modify the Dockerfile for instance) follow the following instructions:

Building the container:

1. Get the DEEP-OC-image-classification-tf repository (this repo):

   $ git clone https://github.com/deephdc/DEEP-OC-image-classification-tf
   

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2. Build the container:

   $ cd DEEP-OC-image-classification-tf
   $ docker build -t deephdc/deep-oc-image-classification-tf .
   

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3. Run the container:

   $ docker run -ti -p 5000:5000 -p 6006:6006 deephdc/deep-oc-image-classification-tf
   

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These three steps will download the repository from GitHub and will build the Docker container locally on your machine. You can inspect and modify the Dockerfile in order to check what is going on. For instance, you can pass the --debug=True flag to the deepaas-run command, in order to enable the debug mode.

⁠Connect to the API

Once the container is up and running, browse to http://localhost:5000 to get the OpenAPI (Swagger)⁠ documentation page. If you are training on your dataset, you can monitor the training progress in Tensorboard connecting to http://localhost:6006.