Hello, community!
I have read posts and blogs in multiple forums about users deploying an object detection model into microcontrollers, mainly ESP32. But all the object detection model tutorials and guides I found were too simple. Detecting only about three objects, and requiring single object images.
What I want to do is to deploy a object detection model with 10 to 12 classes that can detect multiple objects in an image on a Xiao ESP32S3 Sense. For example, let’s say an indoor object detection model that can detect furniture like chair, sofa, lamp, tv, and so on. When prompted an image of a living room taken by the OV3660 camera, it should detect “simultaneously” the sofa, chair, tv, etc. I found the Arduino IDE deployment feature inside Edge Impulse really interesting since it automatically creates an Arduino library for the user. Making it easier to use the model on microcontrollers.
I followed the model training by using these guides. But again, they only use a few classes and require a dataset of single object images:
- XIAO: Big Power, Small Board - 4.5 Object Detection
- Beginners guide to Object Detection with Edge Impulse | by Peter Ing | Medium
I have just begun to use Edge Impulse, Arduino and training ML models. But I am interested in learning more about it!
Does someone know a helpful guide that can help me on that?