Metadata-Version: 2.1
Name: taco-box
Version: 0.1.0
Summary: An implementation library of Tiling and Corruption (TACo) Augmentations for OCR/HTR!
Home-page: https://github.com/kartikgill/taco-box
Author: Kartik Chaudhary
Author-email: kartikgill96@gmail.com
License: UNKNOWN
Description: # Tiling and Corruption (TACo)[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
        `TACo` is a simple and effective data augmentation technique for the task of Optical Character Recognition (`OCR`) or Handwritten Text Recognition (`HTR`) (check reference).
        
        And, `taco-box` is an implementation of `TACo` algorithm. This is currently under the Apache 2.0, Please feel free to use for your project. Enjoy!
        
        ## Installing
        First, you need to have `python 3` installed in your system.
        
        Next, you can Install `taco-box` with `pip` or your favorite PyPi package manager.
        
        ```bash
        pip install taco-box
        ```
        
        ## Usage
        Checkout this jupyter notebook on usage - [Notebook](https://github.com/kartikgill/taco-box/blob/main/tests/Taco_testing.ipynb)
        
        Here is an example: 
        
        ```python
        from tacobox import Taco
        
        # creating Taco object. (Note: parameters are at their default value.)
        mytaco = Taco(cp_vertical=0.25,
                        cp_horizontal=0.25,
                        max_tw_vertical=100,
                        min_tw_vertical=20,
                        max_tw_horizontal=50,
                        min_tw_horizontal=10
                        )
        
        # apply random vertical corruption
        augmented_img = mytaco.apply_vertical_taco(input_img, corruption_type='random')
        mytaco.visualize(augmented_img)
        ```
        
                -------Understanding Arguments--------
                :cp_vertical:        corruption probability of vertical tiles
                :cp_horizontal:      corruption probability for horizontal tiles
                :max_tw_vertical:    maximum possible tile width for vertical tiles in pixels
                :min_tw_vertical:    minimum tile width for vertical tiles in pixels
                :max_tw_horizontal:  maximum possible tile width for horizontal tiles in pixels
                :min_tw_horizontal:  minimum tile width for horizontal tiles in pixels
                
        ## Expected results
        Below picture shows the variations of `TACo` augmentation algorithm from current implementation:-
        
        <p align="center">
          <img src="https://github.com/kartikgill/taco-box/blob/main/images/taco_results.png" alt="Example result of base spectrogram"/ width=600>
        </p>
        
        ## Contributing 
        This project is in very early stages of development. If there is an issue or feature request, feel free to open an issue. Additionally, a PR is always welcome.
        
        ## Reference
        TACo algorithm is part of a research project on Handwritten Text Recognition. Link to the original paper will be posted soon!!
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Description-Content-Type: text/markdown
