gifr release

A lot of our Docker images allow the user to make predictions in two ways: using simple file-polling or via a Redis backend. File-polling is great for testing, but unsuitable for a production system due to wear-and-tear on SSDs.

Initially, I developed a really simple library for sending and receiving data via Redis, called simple-redis-helper:

https://github.com/fracpete/simple-redis-helper

With this library you get some command-line tools for broadcasting, listening, etc. Sufficient for someone who is comfortable with the command-line (or especially when logged in remotely via terminal), but not so great for your clients.

Now, there is the brilliant gradio library that was specifically developed for such scenarios: to create easy to use and great looking interfaces for your machine learning models.

The last couple of days, I have put together a new library that is tailored to our Docker images called gifr:

https://github.com/waikato-datamining/gifr

With the first release, the following types of models are supported:

• image classification

• image segmentation

• object detection/instance segmentation

• text generation