OMR-Datasets | Collection of datasets used for Optical Music Recognition | Dataset library

by apacha Python Version: 1.3.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | OMR-Datasets Summary

OMR-Datasets is a Python library typically used in Artificial Intelligence, Dataset, Deep Learning applications. OMR-Datasets has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

The following datasets are referenced from this repository:. If you find mistakes or know of any relevant datasets, that are missing in this list, please open an issue or directly file a pull request.

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Quality

Security

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Support

OMR-Datasets has a low active ecosystem.

It has 227 star(s) with 37 fork(s). There are 19 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of OMR-Datasets is 1.3.0

Quality

OMR-Datasets has 0 bugs and 27 code smells.

Security

OMR-Datasets has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

OMR-Datasets code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

OMR-Datasets is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

OMR-Datasets releases are available to install and integrate.

Build file is available. You can build the component from source.

OMR-Datasets saves you 4888 person hours of effort in developing the same functionality from scratch.

It has 10300 lines of code, 113 functions and 27 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed OMR-Datasets and discovered the below as its top functions. This is intended to give you an instant insight into OMR-Datasets implemented functionality, and help decide if they suit your requirements.

Generate images from raw data directory
Draws text onto canvas
Returns the full path to the symbol class
Draws the contents of the file
Creates a visual representation of the symbol
Generates images from the given list of symbols
Draws Capitan strokes
Draw the Capitan score bitmap
Extracts and renders all symbols from MUSCIMA
Render nodes from a list of nodes
Finds all XML files in the raw data directory
Load nodes from XML files
Render node masks from muscima
Returns a list of all file paths in the raw data directory
Render nodes for semantic segmentation
Render the image segmentation for the given nodes
Extracts the symbols from an OMR dataset
Extract symbols from an XML file
Returns the bounding box with margin
Download images from MEI
Downloaded EDIR images
Generates the bounding boxes for all images in the given directory
Draws bounding boxes into an image
Get a long description from the README md file
Arguments for homus image generator
Arguments for homus image generation

Get all kandi verified functions for this library.

OMR-Datasets Key Features

No Key Features are available at this moment for OMR-Datasets.

OMR-Datasets Examples and Code Snippets

No Code Snippets are available at this moment for OMR-Datasets.

Community Discussions

Trending Discussions on OMR-Datasets

pip install does not install required dependencies declared with install_requires

QUESTION

pip install does not install required dependencies declared with install_requires

Asked 2020-Jun-02 at 17:32

My question is similar to this question, yet different.

I am the maintainer of the Python package omrdatasettools where I provide users with small helper scripts to perform dataset downloads, etc. My scripts have dependencies on their own, e.g., lxml or tqdm. I want people to be able to install my library and use it, however when you create a new conda environment and call pip install omrdatasettools the installation fails because it does not find the necessary packages.

What I've done so far: I've added all necessary libraries into the install_requires-section of my setup.py

...

ANSWER

Answered 2020-Jun-02 at 17:32

You do import omrdatasettools in your setup.py, omrdatasettools/__init__.py imports .Downloader and omrdatasettools/Downloader.py imports lxml which is not yet installed.

Short resume: do not import (directly or indirectly) uninstalled modules in setup.py.

Ways to workaround:

Do not import your submodules in __init__.py so when setup.py imports omrdatasettools it only imports __init__.py but not submodules.
In your setup.py you probably only need the version so do not import it but read from a file. You can even read it from a Python module by evaluating code without triggering import from __init__.py. Like this:

Source https://stackoverflow.com/questions/62154670

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install OMR-Datasets

You can download it from GitHub.
You can use OMR-Datasets like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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