2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement | BDCI Contest Best Innovation Exploration Award Winner

by Mingtzge Python Version: Current License: MIT

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

kandi X-RAY | 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement Summary

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement is a Python library. 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement build file is not available. You can download it from GitHub.

2019CCF-BDCI Contest Best Innovation Exploration Award Winner Based on OCR ID Card Element Extraction Competition Champion Tianchen Poxiao Team Competition Question Source Code

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Quality

Security

License

Reuse

Support

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement has a medium active ecosystem.

It has 853 star(s) with 315 fork(s). There are 26 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 36 have been closed. On average issues are closed in 29 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement is current.

Quality

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement has no bugs reported.

Security

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement 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

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement releases are not available. You will need to build from source code and install.

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement has no build file. You will be need to create the build yourself to build the component from source.

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

Top functions reviewed by kandi - BETA

kandi has reviewed 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement and discovered the below as its top functions. This is intended to give you an instant insight into 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement implemented functionality, and help decide if they suit your requirements.

Train a dataset
Feature sequence extraction
Inverse inference function
Compute the ctc loss
Display the current visualization
Add images
Save a numpy array
Add a text header
Run watermask removal
Detect train_fn
Define the discriminator layer
R Define the G
Process one image
Write tf records to disk
Saves visuals to HTML
Judge the image of the given img_path
Process cut - twist images
Parse options
Plot the current loss for a given epoch
Run train and test
Print the current loss
Save all the networks
Modify commandline options
List all label ids for a given split
Optimizes parameters
Create a model instance
Return the palette for the given label

Get all kandi verified functions for this library.

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement Key Features

No Key Features are available at this moment for 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement.

2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement Examples and Code Snippets

No Code Snippets are available at this moment for 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement.

Community Discussions

No Community Discussions are available at this moment for 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement

You can download it from GitHub.
You can use 2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement 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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