SimpleHTR | Handwritten Text Recognition system | Computer Vision library

by githubharald Python Version: Current License: MIT

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

kandi X-RAY | SimpleHTR Summary

SimpleHTR is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow applications. SimpleHTR has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Update 2021/2: recognize text on line level (multiple words). Update 2021/1: more robust model, faster dataloader, word beam search decoder also available for Windows. Update 2020: code is compatible with TF2. Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset. The model takes images of single words or text lines (multiple words) as input and outputs the recognized text. 3/4 of the words from the validation-set are correctly recognized, and the character error rate is around 10%.

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Quality

Security

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Support

SimpleHTR has a medium active ecosystem.

It has 1633 star(s) with 806 fork(s). There are 52 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 136 have been closed. On average issues are closed in 5 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SimpleHTR is current.

Quality

SimpleHTR has 0 bugs and 0 code smells.

Security

SimpleHTR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

SimpleHTR code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SimpleHTR 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

SimpleHTR 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.

SimpleHTR saves you 228 person hours of effort in developing the same functionality from scratch.

It has 560 lines of code, 34 functions and 5 files.

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

Top functions reviewed by kandi - BETA

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

Process image data .
Infer the model .
Train a model .
Train the CTC model .
Validate the model .
Parse command line arguments .
Infer a model .
Return a numpy array from the samples
Get the size of the image .
Writes the character error rates .

Get all kandi verified functions for this library.

SimpleHTR Key Features

No Key Features are available at this moment for SimpleHTR.

SimpleHTR Examples and Code Snippets

No Code Snippets are available at this moment for SimpleHTR.

Community Discussions

Trending Discussions on SimpleHTR

How to troubleshoot TensorFlow error “Restoring from checkpoint failed.”

QUESTION

How to troubleshoot TensorFlow error “Restoring from checkpoint failed.”

Asked 2020-Jun-26 at 19:37

I am new to Tensorflow, I have been using a trained model from a Git repository. The pre-trained model is saved in '../model/snapshot-38' directory. I have snapshot-38.index, snapshot-38.meta, snapshot-38.data-00000-of-00001 and checkpoint files here. I have my python script files and data in '../src' and I don't use any other location other than these in my code to save model.

...

ANSWER

Answered 2020-Jun-26 at 08:41

The error says this: Assign requires shapes of both tensors to match. lhs shape= [1,1,512,71] rhs shape= [1,1,512,80]

This means that the dimensions of one of the tensors in the snapshot are different from the tensor in the model, in the snapshot it is [1,1,512,80] and in the model it is [1,1,512,71].

Therefore, something is different. You have to load the snapshot on a model that matches exactcly the one it was saved from.

If I would have to guess, I would say that this is a multi-class classification model and that the number of classes the model was trained in (i.e. the snapshot) was 80, while now the model has been built to classify 71 classes.

Source https://stackoverflow.com/questions/62601746

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

Vulnerabilities

No vulnerabilities reported

Install SimpleHTR

You can download it from GitHub.
You can use SimpleHTR 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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