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https://community.dfrobot.com/makelog-314441.html
Description:
Welcome to our latest project featuring the innovative UNIHIKER Linux Board! In this video, we demonstrate how to use AI to enhance electronics recognition in a real-world factory setting. ✨
What You'll Learn:
AI Integration:See how artificial intelligence is applied to identify electronic components.
Smart Imaging: Watch as our system takes photos and accurately finds component leads.
Efficiency Boost: Discover how this technology streamlines manufacturing processes and reduces errors. Why UNIHIKER?
The UNIHIKER Linux Board provides a robust platform for running AI algorithms, making it ideal for industrial applications. Its flexibility and power enable precise component recognition, ensuring quality and efficiency in production.
? Applications: Perfect for electronics engineers, factory automation, and anyone interested in the intersection of AI and electronics.
STEP 1:Test Usb camera & Test OpenCV
Since I have an old, second-hand USB camera that I bought at a cheap price and haven't used, I decided to test if the UNIHIKER board can work with the camera. This will help determine if I can use it for this project and also test the OpenCV capabilities included with this board.
STEP 2:Training models
TensorFlow is an open-source library developed by Google for building deep learning
and machine learning models.It is well-suited for tasks that
require high computational power and the processing of large datasets.
TensorFlow Lite is a lightweight version of TensorFlow designed for deploying AI models on resource-constrained devices, such as mobile phones, microcontrollers, and IoT devices.
It focuses on high-efficiency performance with low power consumption. TensorFlow Lite is used to deploy models developed with TensorFlow onto end devices with limited resources. It is ideal for applications that require real-time responses, such as image processing, voice detection, and speech recognition.
https://teachablemachine.withgoogle.com/
STEP 3:Install all related files
sudo apt-get updatepip install unihiker
pip install pinpongpip install -U pinpong
pip install tflite-runtime
STEP 4:Source Code
Code:
https://github.com/YakrooThai/UNIHIKER/tree/main/SmartECG
You can contactE-mail: mhooyang@gmail.com
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