Ayush Adhikari

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Ayush Adhikari

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Monday, May 19, 2025

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Handwritten Letters to 3D-Printed Braille Letters

This is a team project for my CS370 class that involved the use of a Raspberry Pi to communicate and coordinate two external devices. I acted as the team leader and inititated the project, managed the repository for the project, and coordinated the tasks of each member. The goal of the project was to use a camera to take a picture of some handwritten text, which is then uploaded to the Raspberry Pi. Using Python, we would preprocess the image, and use OpenCV to find and extract contours, leading to individual letters of specific size. The letters would then be sequentially classified by a convolutional neural network trained using the EMNIST dataset on handwriting. After this, the letters are combined using stl models into a single 3D model along the y-direction. We used slic3r to slice the stl file into gcode using the shell and sent that to the Raspberry Pi using ssh and sftp. The pi would then serially send each line of gcode to the printer to be printed.

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This is a feature mainly used to demonstrate the use of the handwriting app built using a canvas and CNN. You can use the search bar to search the site for content or to navigate the site by typing in a word such as home, which will take you to the home page. Below the search bar is a canvas where you can draw letters. This is implemented using a digit recognition CNN. As the accuracy is around 89 percent, it might not always produce an accuracte prediction, for example between o and 0. You can use the three button next to the search bar to delete the last character, clear the search bar, and finally search the site.