![]() If your needs are simple, you may be able to fulfill them with an inexpensive ESP32-CAM board. Today we’ll see that even the ESP32 is capable of simple object detection. ![]() We’ve already seen how well the Kendryte K210 performs in the DFRobot Husky Lens using this technique. This sort of hardware is required to run the neural networks needed for machine learning.īut now we have a new generation of microcontrollers that can run a small version of machine language, something called Embedded ML or Tiny ML. We have also used SBCs like the NVIDIA Jetson Nano, which is essentially an AI-dedicated GPU, for these tasks. Only a few years ago, “playing” with applications like this demanded huge computers, often with big (and expensive) graphics cards. One such technology is Object Detection, the ability of a machine to recognize an object (or several objects) using a video camera. When trying to keep pace with the dizzying speed of technology, one thing that never ceases to amaze me is how a cutting-edge application can go from costing millions of dollars to costing pennies, all in the space of a few years. Today we’ll see how to use Edge Impulse to train an ESP32-CAM board to detect objects. ![]() This 9-dollar camera board is probably already in your parts’ drawer, and with the right training, it can be used for simple Object Detection. If you’re after a simple and inexpensive Object Detection system, consider using an ESP32-CAM. 7 Capturing Images (Webcam & Edge Impulse).4 Object Detection using Microcontrollers.
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