An image recognition system developed with python and ML libraries to detect music notations. It is connected along with a web application using flask and it was developed for an academic project.
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Table of Contents
- [Python]
- [OpenCV]
- [TensorFlow]
- [Numpy]
- [Flask]
- [HTML]
- [CSS]
- [JavaScript]
To get a local copy up and running follow these simple example steps.
This project is built using Python. You may need to have installed python and pip to install required packages.
- Get Python and pip
- Clone the repo and resolve dependencies, if any
git clone https://github.com/sayuru-akash/music-notation-recognizer.git
- Install dependencies
- Train the model
python3 train.py \
--bottleneck_dir=logs/bottlenecks \
--how_many_training_steps=2000 \
--model_dir=inception \
--summaries_dir=logs/training_summaries/basic \
--output_graph=logs/trained_graph.pb \
--output_labels=logs/trained_labels.txt \
--image_dir=./dataset
- Run the web application
python3 classify_webcam.py
This project can be used to recognize music notation images.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
This project is an academic project done on 2021 and is contributed by
Distributed under the GPL-3.0 License. See LICENSE
for more information.
Sayuru Akash - @sayuru_akash - contact@sayuru.me
Project Link: https://github.com/sayuru-akash/music-notation-recognizer