BlueStamp2021

This is a Raspberry Pi project that was completed at BlueStamp Engineering in July 2021.

View the Project on GitHub tyzhou05/BlueStamp2021

Chess Board Detection with TensorFlow and Raspberry Pi

chessboard

This project uses a Raspberry Pi to detect and re-format chess boards, and it was created in 3 weeks through an online program at BlueStamp Engineering. Overall, I was able to implement two different programs, which allow my Raspberry Pi to detect general images, and also convert Chessboards into more simple formats. I learned tons about Raspberry Pi, machine learning, debugging, and engineering in general!

Engineer School Area of Interest Grade
Tony Z. Valley Christian High School Computer Science/Engineering Incoming Junior

Final Milestone

After looking at different ways to create and train a custom object detection model, I soon realized that it would take too much time. I then looked online, and was able to find a very interesting model that took a chessboard, compressed it, and converted it into an online format using a neural network in TensorFlow. Over the next few days, I worked on training and testing this custom model, and once I finished, I found out that the FEN(notation system for chess boards online) algorithm was private, and I realized that trying to create my own algorithm would take too much time.

milestoneboard

Before detection

milestoneboardafter

After detection!

milestone3running

The model training and running, showing accuracy

Second Milestone

For my second milestone, I first started by following this article to set up TensorFlow, an open-source machine learning database for object detection. I soon ran into some problems involving downloading the now updated version of the TensorFlow model through GitHub, which had been modified extensively since the article was published. I spent multiple days debugging and trying to figure out solutions to it, and I was finally able to find a much better tutorial, which allowed me to detect objects through images and videos! I then was able to set up my Raspberry Pi Camera, and the software also worked through a live feed and was able to detect objects in my room. Although Google’s public detection model works well for common objects, there were still some errors(such as detecting a bird feeder as a fire hydrant), so for my next milestone, I am planning on creating and training my own object detection model.

milestone2farm

A pretty good detection!

milestone2sheep

Another pretty good detection!

First Milestone

My first milestone was being able to setup my Raspberry Pi. I was able to unpack my materials, and first download Raspian to an SD card for my Raspberry Pi. I then connected my Raspberry Pi to power, a second HDMI monitor, and an Amazon Basic keyboard and mouse set. I then was able to set up VNC, a software that allows me to view my Raspberry Pi from a window on my main laptop monitor instead of through my second monitor, which makes life a lot easier! For my next steps, I plan to install TensorFlow and get started with object detection.

milestone1pi

My Raspberry Pi setup

milestone1setup

My second monitor setup