#AI – Mis posts sobre CustomVision.ai, exportando y utilizando ONNX, Docker, en PC, RaspberryPi, MacOS y más !

Buenas !

Ahora que tengo una pausa entre eventos en Canada y USA, y ya he escrito varios posts al respecto, es el tiempo ideal para compilar y compartir los posts que he escrito sobre CustomVision.ai. Sobre como crear un proyecto de reconocimiento de objectos, como utilizar el mismo en modo web, invocando un HTTP Endpoint desde una app de consola. Y también desde aplicaciones en Windows 10 exportando el proyecto a formato ONNX y utilizando Windows ML. Finalmente, un par de post donde explico como utilizar CV.ai con docker en PC, Mac y Raspberry Pi.

1. Object recognition with Custom Vision and ONNX in Windows applications using WinML
2. Object recognition with Custom Vision and ONNX in Windows applications using WinML
3. Object recognition with Custom Vision and ONNX in Windows applications using Windows ML, drawing frames
4. Object recognition with Custom Vision and ONNX in Windows applications using Windows ML, calculate FPS
5. Can’t install Docker on Windows 10 Home, need Pro or Enterprise
6. Running a Custom Vision project in a local Docker Container
7. Analyzing images in a Console App using a Custom Vision project in a Docker Container
8. Analyzing images using PostMan from a Custom Vision project hosted in a Docker Container
9. Building the CustomVision.ai project in Docker in a RaspberryPi
10. Container dies immediately upon successful start in a RaspberryPi. Of course, it’s all about TensorFlow dependencies
11. About ports, IPs and more to access a container hosted in a Raspberry Pi
12. 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

Greetings @ Burlington

El Bruno