checkout-data-generation | prepare synthetic data for training classifiers

by ShiZiqiang Python Version: Current License: GPL-3.0

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kandi X-RAY | checkout-data-generation Summary

checkout-data-generation is a Python library. checkout-data-generation has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

This repo is to prepare synthetic data for training classifiers and detectors used in Details on how to generate the data can be found in our paper "CheckSORT: Refined Synthetic Data Combination and Optimized SORT for Automatic Retail Checkout".

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Support

checkout-data-generation has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

checkout-data-generation has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of checkout-data-generation is current.

Quality

checkout-data-generation has no bugs reported.

Security

checkout-data-generation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

checkout-data-generation is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

checkout-data-generation releases are not available. You will need to build from source code and install.

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

Installation instructions are not available. Examples and code snippets are available.

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checkout-data-generation Key Features

No Key Features are available at this moment for checkout-data-generation.

checkout-data-generation Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install checkout-data-generation

You can download it from GitHub.
You can use checkout-data-generation 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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