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Orchestra is a sheet music reader (optical music recognition (OMR) system) that converts sheet music to a machine-readable version.

License: MIT License

Python 100.00%
omr omr-sheet optical-character-recognition optical-music-recognition image-processing cv2 detection segmentation machine-learning hemdan

orchestra's Introduction

Orchestra

GitHub contributors GitHub issues GitHub forks GitHub stars GitHub license

About

Orchestra is a sheet music reader (optical music recognition (OMR) system) that converts sheet music to a machine-readable version.

image

How it works

List of steps we take to process the input sheet and get our results

1. Noise Removal

1  noise_removed

2. Binarization

2  binarized

3. Staff line removal

3  cleaned

4. Cutted buckets


4  cutted-1



4  cutted-2



4  cutted-3



5. Segmentation and detection

colored_0_1


colored_0_2


colored_0_3

6. Recognition

  1. Cutted 1

[ \meter<"4/4"> d1/4 e1/32 e2/2 e1/8 e1/16 e1/32 {e1/4,g1/4} e1/4 e1/8 c1/8 g1/32 c1/16 e1/32 ]

  1. Cutted 2

[ \meter<"4/4"> {e1/4,g1/4,b1/4} a1/8 d1/8 c1/16 g1/16 d1/16 e1/16 c2/16 g2/16 d2/16 e2/16 {f1/4,g1/4,b1/4} c1/4 a1/4. a1/8 a1/32.. ]

  1. Cutted 3

[ \meter<"4/4"> e1/16 e1/16 e1/16 e1/16 e1/4 e#1/4 g1/4 g&&1/4 g1/4 e#2/4 ]

Installation

  1. Clone the repository
$ git clone https://github.com/AbdallahHemdan/Orchestra.git
  1. Navigate to repository directory
$ cd Orchestra
  1. Install dependencies
$ pip install -r requirements.txt

Running

  1. Put you input files inside input folder

  2. Put you output files inside output folder

  3. Running

python main.py $path_of_input_folder $path_of_output_folder

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

Check out our contributing guidelines for ways to contribute.

Contributors


Abdallah Hemdan


Adel Mohamed


Kareem Mohamed^3


Ahmed Mahboub

Licence

MIT Licence

orchestra's People

Contributors

abdallahhemdan avatar adelrizq avatar kareem3m avatar mahboub99 avatar satinwukerorig avatar

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orchestra's Issues

Model.sav Not found

I am trying to run the program, but am getting this error:

model = pickle.load(open(filename, 'rb'))
FileNotFoundError: [Errno 2] No such file or directory: 'model/model.sav'

I have checked the model folder and model.sav seems to be there, so I am unaware of what might be causing this error

What should I put in the output folder

hello,i am a music conservatory student and i am trying to figure out how the OMR system work. So what make me confused is that i input the sheet photos to convert it into other formats,but what should i put in the output folder?

Error running the demo

python main.py input output
/Users/jli/miniconda3/envs/simage/lib/python3.7/site-packages/sklearn/base.py:318: UserWarning: Trying to unpickle estimator LinearSVC from version 0.23.1 when using version 0.22.2.post1. This might lead to breaking code or invalid results. Use at your own risk.
UserWarning)
too many values to unpack (expected 2)
input-01.PNG has been failed !!
too many values to unpack (expected 2)
input-03.PNG has been failed !!

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