Deploy the Model
Once you have validated your trained model, take a look at examples of deploying this model across different platforms. You can find a checklist of supported devices. We support validation on specific targets and applications for live video inference with links provided below.
| Platform | On Target Validation | Live Video | In Development |
|---|---|---|---|
| PC / Linux | ✓ | ||
| Mac/MacOS | ✓ | ||
| i.MX 8M Plus EVK | ✓ | ✓ | |
| NVIDIA Orin | ✓ | ||
| Kinara ARA-2 | ✓ | ||
| Raivin Radar Fusion | ✓ | ✓ | ✓ |
| i.MX 95 EVK | ✓ | ✓ |
Additional Platforms
Certain platforms are still under development and support for platforms beyond these listed will be available soon. Let us know which platform you'd like to see supported next!
In this Quickstart guide, you have created your EdgeFirst Studio account, logged in to EdgeFirst Studio, and created your very first project and ran your first experiment by copying a sample dataset and trained and validated a Vision model using the copied dataset. Finally you explored several options for deploying your trained model in different hardware platforms.
Next Steps
Now that you have reached the end of the Quickstart guide, learn more about EdgeFirst Studio. Ready for more advanced end-to-end workflows? Follow along the User Workflows that are tailored towards various hardware requirements and resources available to the user.