Object classification and counting are essential for factory automation and devices where different objects are sorted or counted during packaging. Factories producing buttons, chocolates, and similar items require accurate counting for efficient packaging, which is a time-consuming and costly process when done manually.
Implementing an automation system to detect, classify, sort, and count objects can significantly streamline the production process. This project aims to create a cost-effective device for implementing such a factory automation system.
Object classifications are easily achievable using Edge Impulse models. You can distinguish between a man and an animal, a bicycle and other types of vehicles, and so on.
In our previous article, we did the same
Similarly, you can accurately count one type of object among other types.
Initially designed for MCU-level implementation on devices like ESP32 and Arduino Nicla Vision, the project was intended for counting a small area of 120 pixels x 120 pixels, with a relatively small-sized button as the object of interest.
However, it became apparent that even for this small area, the MCUs were inadequate, as the model file itself is approximately 8MB long. Consequently, the project was eventually installed on a Raspberry Pi computer, where it operates seamlessly. Refer to Fig. 1 for an illustration of the author’s working prototype.
Please register to view this article or log in below. Tip: Please subscribe to EFY Prime to read the Prime articles.
