This tutorial uses a single container to deploy the TinyYolo model on the Intel UP2 device.
In this example a sample container is built using the Azure Machine Learning Service.
1. An Azure Account Subscription (with pre-paid credits or billing through existing payment channels)
Set up the account in Azure portal using this tutorial.
- Your subscription must have pre-paid credits or bill through existing payment channels. (If you make an account for the first time, you can get 12 months free and $200 in credits to start with.)
2. Setup Jupyter Environment to run this tutorial notebook.
1. If you have an Azure Machine Learning service workspace, skip to step #2. Otherwise, create one now.
- Sign in to the [Azure portal](https://portal.azure.com) by using the credentials for the Azure subscription you use.
- In the upper-left corner of the portal, select __Create a resource__.
- In the search bar, enter __Machine Learning__. Select the __Machine Learning service workspace__ search result.
- In the __ML service workspace__ pane, scroll to the bottom and select Create to begin.
- In the __ML service workspace__ pane, configure your workspace and select __Create__. It can take a few minutes to create the workspace. When the process is finished, a deployment success message appears. It's also present in the notifications section. To view the new workspace, select __Go to resource__.
2. Create a cloud-based notebook server.
- Open your Machine Learning workspace in the Azure portal.
- On your workspace page in the Azure portal, select __Notebook VMs__ on the left.
- Select __+New__ to create a notebook VM.
- Provide a name for your VM and select __Create__.
- Wait approximately 4-5 minutes until the status changes to __Running__
3. Launch the Jupyter wed interface in your Notebook VM
- Select __Jupyter__ in the __URI__ column for your VM.
- On the Jupyter notebook webpage, the top foldername is your username.
More details about quickstart setup instructions are located [here](https://docs.microsoft.com/en-us/azure/machine-learning/service/quickstart-run-cloud-notebook).
From the Notebook VM launch the Jupyter web interface as descriped in step #3 above. Click New -> Terminal on the upper right corner of the web interface. You will get a new browser tab with the bash prompt.
You can use regular git clone --recursive https://github.com/Azure-Samples/onnxruntime-iot-edge
command line commands to clone this repository into a desired folder.
Open the notebook AzureML-OpenVINO/AML-BYOC-ONNXRUNTIME-OpenVINO.ipynb
and start executing the cells.