Getting started with Computer Vision AI / ML — Tutorial Step 4 of 7: Download the model from Google’s platform
In this tutorial, we learn how to create a system to detect if a sink contains any dishes that need washing up. This is step 4 of 7. Start with Step 1 here, or view the full tutorial on Gravio.com.
Steps to get into Machine Learning and Computer Vision
- Collecting images of as many different situations as possible (Details)
- Setting up your Google Cloud Vision account (Details)
- Uploading and labeling those images via the Google Vision AI website, training the Model (Details)
- Download the model from Google’s platform 👈 YOU ARE HERE
- Set up Gravio Coordinator and connect HubKit to it (Details)
- Deploy the model to Gravio Coordinator and subsequently to HubKit (Details)
- Create Actions that are being triggered based on what the camera sees (Details)
Step 4 — Download the model from Google’s platform
If your model works well, you can download your model to your computer for the deployment on your Gravio or any other platform that takes the Tensorflow files. You will need the “Tensorflow Lite” files for Gravio.
In order to do that you will need to install “gsutil” on your computer. Please follow the instructions for your operating system on the website from Google: https://cloud.google.com/storage/docs/gsutil_install
Once that’s installed and authenticated, you can use the command
gsutil cp -r gs://<name-of-your-bucket> ./<destination_folder>
To download the models that Google has created for you. It will look something like this:
That’s it, you’re ready to deploy the model and use it. In the following steps we will show you how to deploy them on the Gravio Edge Computing infrastructure.
Continue to the next Step: Set up Gravio Coordinator and connect HubKit to it
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