Document processing using transformers

Last update: Dec 21, 2022

Related tags

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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v-7(Oct 7, 2021)

Source code(tar.gz)
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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)

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

Fixed bugs and updates
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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

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Document processing using transformers

Related tags

Overview

Doc Transformers

Pre-requisites

Implementation

Results

You might also like...

CDLA: A Chinese document layout analysis (CDLA) dataset

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This project uses word frequency and Term Frequency-Inverse Document Frequency to summarize a text.

Bnagla hand written document digiiztion

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This repository serves as a place to document a toy attempt on how to create a generative text model in Catalan, based on GPT-2

This repository contains all the source code that is needed for the project : An Efficient Pipeline For Bloom’s Taxonomy Using Natural Language Processing and Deep Learning

We have built a Voice based Personal Assistant for people to access files hands free in their device using natural language processing.

Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5

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)

v-1(Sep 2, 2021)

v-2(Sep 2, 2021)

Owner

Vishnu Nandakumar

Huggingface Transformers + Adapters = ❤️

DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time

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