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Thomas Dehaene
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Add app
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README.md
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---
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title:
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emoji:
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colorFrom:
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colorTo:
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sdk: streamlit
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app_file: app.py
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pinned: false
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---
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# Configuration
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`title`: _string_
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Display title for the Space
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`emoji`: _string_
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Space emoji (emoji-only character allowed)
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`colorFrom`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`colorTo`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`sdk`: _string_
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Can be either `gradio` or `streamlit`
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`sdk_version` : _string_
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Only applicable for `streamlit` SDK.
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See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
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`app_file`: _string_
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Path to your main application file (which contains either `gradio` or `streamlit` Python code).
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Path is relative to the root of the repository.
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`pinned`: _boolean_
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Whether the Space stays on top of your list.
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title: ByT5 dOCRtor
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emoji: π
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colorFrom: red
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colorTo: yellow
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sdk: streamlit
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app_file: app.py
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pinned: false
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---
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# Configuration
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`title`: _string_
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Display title for the Space
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`emoji`: _string_
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Space emoji (emoji-only character allowed)
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`colorFrom`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`colorTo`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`sdk`: _string_
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Can be either `gradio` or `streamlit`
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`sdk_version` : _string_
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Only applicable for `streamlit` SDK.
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See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
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`app_file`: _string_
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Path to your main application file (which contains either `gradio` or `streamlit` Python code).
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Path is relative to the root of the repository.
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`pinned`: _boolean_
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Whether the Space stays on top of your list.
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app.py
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from textwrap import wrap
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import streamlit as st
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from transformers import pipeline
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import nlpaug.augmenter.char as nac
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st.markdown('# ByT5 Dutch OCR Corrector :pill:')
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st.write('This app corrects common dutch OCR mistakes, to showcase how this could be used in an OCR post-processing pipeline.')
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st.markdown("""
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To use this:
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- Enter a text with OCR mistakes and hit 'unscramble':point_down:
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- Or enter a normal text, scramble it :twisted_rightwards_arrows: and then hit 'unscramble' :point_down:""")
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@st.cache(allow_output_mutation=True,
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suppress_st_warning=True,
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show_spinner=False)
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def load_model():
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with st.spinner('Please wait for the model to load...'):
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ocr_pipeline=pipeline(
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'text2text-generation',
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model='ml6team/byt5-base-dutch-ocr-correction',
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tokenizer='ml6team/byt5-base-dutch-ocr-correction'
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)
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return ocr_pipeline
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ocr_pipeline = load_model()
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if 'text' not in st.session_state:
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st.session_state.text = ""
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left_area, right_area = st.columns(2)
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# Format the left area
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left_area.header("Input")
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form = left_area.form(key='ocrcorrector')
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placeholder = form.empty()
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placeholder.empty()
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input_text = placeholder.text_area(value=st.session_state.text, label='Insert text:', key='input_text')
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scramble_button = form.form_submit_button(label='Scramble')
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submit_button = form.form_submit_button(label='Unscramble')
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# Right area
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right_area.header("Output")
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if scramble_button:
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aug = nac.OcrAug()
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st.session_state.text = st.session_state.input_text
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base_text = st.session_state.text
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augmented_data = aug.augment(base_text)
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st.session_state.text = augmented_data
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del st.session_state.input_text
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placeholder.empty()
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input_text = placeholder.text_area(value=st.session_state.text, label='Insert text:', key='input_text')
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if submit_button:
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base_text = st.session_state.input_text
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output_text = " ".join([x['generated_text'] for x in ocr_pipeline(wrap(base_text, 128))])
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right_area.markdown('#####')
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right_area.text_area(value=output_text, label="Corrected text:")
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