https://github.com/coding-ai/raspberrypi_handwritten_recognition

Virtual Pen + Recognition of handwritten digits
https://github.com/coding-ai/raspberrypi_handwritten_recognition

artificial-intelligence computer-vision handwriting-recognition handwritten-character-recognition handwritten-digit-recognition image-processing machine-learning machine-learning-algorithms mnist mnist-handwriting-recognition model python python37 raspberry-pi raspberry-pi-4 raspberry-pi-camera

Last synced: 3 months ago
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Virtual Pen + Recognition of handwritten digits

• Host: GitHub
• URL: https://github.com/coding-ai/raspberrypi_handwritten_recognition
• Owner: coding-ai
• Created: 2020-05-27T18:45:33.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T01:23:57.000Z (about 2 years ago)
• Last Synced: 2024-09-29T00:42:24.754Z (4 months ago)
• Topics: artificial-intelligence, computer-vision, handwriting-recognition, handwritten-character-recognition, handwritten-digit-recognition, image-processing, machine-learning, machine-learning-algorithms, mnist, mnist-handwriting-recognition, model, python, python37, raspberry-pi, raspberry-pi-4, raspberry-pi-camera
• Language: Python
• Homepage:
• Size: 16.6 KB
• Stars: 9
• Watchers: 4
• Forks: 1
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

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README

        
# Handwritten Recognition with Raspberry Pi

The idea of this project was to create a virtual pen and apply a handwritten recognition model in the backend to recognize handwritten digits from a Raspberry Pi camera.

I have adapted the code created by the amazin people at LearnOpenCV: [Create a Virtual Pen And Eraser with OpenCV](https://www.learnopencv.com/creating-a-virtual-pen-and-eraser-with-opencv/) to predict the written images. 

## Requirements

Run `conda env create` to create the virtual environment with the requirements from `requirements.txt`.

## Steps

Following the steps from the mentioned tutorial, run the following lines:

`python step1.py` - remember to press the 's' key to save your color range image.

`python step2.py`

`python step3.py` and now you can play and predict!

## Suggestions

Please open an issue if you have ideas on how to improve this! Have fun!