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)
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v-8(Oct 7, 2021)

Source code(tar.gz)
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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)

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

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v-1(Sep 2, 2021)

Initial release
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v-2(Sep 2, 2021)

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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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Document processing using transformers

Related tags

Overview

Doc Transformers

Pre-requisites

Implementation

Results

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Releases(v-7)

v-7(Oct 7, 2021)

v-8(Oct 7, 2021)

v-4(Oct 5, 2021)

v-5(Oct 5, 2021)

v-6(Oct 5, 2021)

v-3(Sep 11, 2021)

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Owner

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