Document processing using transformers

Last update: Dec 21, 2022

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Overview

Doc Transformers

Document processing using transformers. This is still in developmental phase, currently supports only extraction of form data i.e (key - value pairs)

pip install -q doc-transformers

Pre-requisites

Please install the following seperately

sudo apt install tesseract-ocr
pip install -q detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu101/torch1.8/index.html

Implementation

# loads the pretrained dataset also 
from doc_transformers import form_parser

# loads the image
image = form_parser.load_image(input_path_image)

# gets the bounding boxes, predictions and image processed
bbox, preds, image = form_parser.process_image(image)

# returns image as the output
im = form_parser.visualize_image(bbox, preds, image)

Results

Input

Output

Please note that this is still in development phase and will be improved in the near future

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Releases(v-7)

v-7(Oct 7, 2021)

Source code(tar.gz)
Source code(zip)
v-8(Oct 7, 2021)

Source code(tar.gz)
Source code(zip)
v-4(Oct 5, 2021)

Added extraction capability
Source code(tar.gz)
Source code(zip)
v-5(Oct 5, 2021)

Fixed bugs
Source code(tar.gz)
Source code(zip)
v-6(Oct 5, 2021)

Source code(tar.gz)
Source code(zip)
v-3(Sep 11, 2021)

Fixed bugs and updates
Source code(tar.gz)
Source code(zip)
v-1(Sep 2, 2021)

Initial release
Source code(tar.gz)
Source code(zip)
v-2(Sep 2, 2021)

updated release
Source code(tar.gz)
Source code(zip)

Owner

Vishnu Nandakumar

Machine learning engineer with competent knowledge in innovating solutions capable of improving business decisions in various domains. Substantial hands-on

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