YOLOv5 🚀 on AzureML
This guide provides a quickstart to use YOLOv5 from an AzureML compute instance.
Note that this guide is a quickstart for quick trials. If you want to unlock the full power AzureML, you can find the documentation to:
You need an AzureML workspace.
Create a compute instance
From your AzureML workspace, select Compute > Compute instances > New, select the instance with the resources you need.
Open a Terminal
Now from the Notebooks view, open a Terminal and select your compute.
Setup and run YOLOv5
Now you can, create a virtual environment:
Clone YOLOv5 repository with its submodules:
Install the required dependencies:
Train the YOLOv5 model:
Validate the model for Precision, Recall, and mAP
Run inference on images and videos:
Export models to other formats:
Notes on using a notebook
Note that if you want to run these commands from a Notebook, you need to create a new Kernel and select your new Kernel on the top of your Notebook.
If you create Python cells it will automatically use your custom environment, but if you add bash cells, you will need to run
source activate <your-env> on each of these cells to make sure it uses your custom environment.