Hi !
I was planning to write a couple of posts about Artificial Intelligence features in the Microsoft Suite, when I checked this feature available in CustomVision.ai.
Last year, Microsoft released a program named [Vision AI Developer Kit for IoT Solution Makers]
Integrated with Azure IoT Edge and working with the Microsoft Azure Machine Learning service (public preview), this Azure IoT Starter kit enables developers to build vision AI solution and run their AI models on the device.
The device uses the Qualcomm vision intelligence platform for hardware acceleration of the AI model to deliver superior inferencing performance. And is specifically designed to deploy AI models built using Azure Machine Learning with Azure IoT Edge.
I just realize that you can also deploy to this camera, ONNX models from Azure AI Gallery, Azure ML models and of course, custom models created using CustomVision.ai. It’s all supported and managed using Azure IoT Edge.
So, now it’s time to check my delivery dates to see how much time I need to wait for my device to arrive and start to check the export option available in the CustomVision.ai portal!
Happy Coding!
Greetings @ Burlington
El Bruno
References
- Microsoft Blog, Accelerating AI on the intelligent edge: Microsoft and Qualcomm create vision AI developer kit
- Vision AI Developer Kit for IoT Solution Makers
- IoT in Action, The AI Camera by eInfochips™– Webinar
My posts on Custom Visopn
- Object recognition with Custom Vision and ONNX in Windows applications using WinML
- Object recognition with Custom Vision and ONNX in Windows applications using WinML
- Object recognition with Custom Vision and ONNX in Windows applications using Windows ML, drawing frames
- Object recognition with Custom Vision and ONNX in Windows applications using Windows ML, calculate FPS
- Can’t install Docker on Windows 10 Home, need Pro or Enterprise
- Running a Custom Vision project in a local Docker Container
- Analyzing images in a Console App using a Custom Vision project in a Docker Container
- Analyzing images using PostMan from a Custom Vision project hosted in a Docker Container
- Building the CustomVision.ai project in Docker in a RaspberryPi
- Container dies immediately upon successful start in a RaspberryPi. Of course, it’s all about TensorFlow dependencies
- About ports, IPs and more to access a container hosted in a Raspberry Pi
- Average response times using a CustomVision.ai docker container in a RaspberryPi and a PC
Windows 10 and YOLOV2 for Object Detection Series
- Introduction to YoloV2 for object detection
- Create a basic Windows10 App and use YoloV2 in the camera for object detection
- Transform YoloV2 output analysis to C# classes and display them in frames
- Resize YoloV2 output to support multiple formats and process and display frames per second
- How to convert Tiny-YoloV3 model in CoreML format to ONNX and use it in a Windows 10 App
- Updated demo using Tiny YOLO V2 1.2, Windows 10 and YOLOV2 for Object Detection Series
- Alternatives to Yolo for object detection in ONNX format
El Bruno 