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import streamlit as st #Web App
from main import classify
#title
st.title("Easy OCR - Extract Text from Images")
#subtitle
st.markdown("## Optical Character Recognition - Using `easyocr`, `streamlit` - hosted on 🤗 Spaces")
model_name = st.selectbox(
'Select a pre-trained model',
[
'finiteautomata/bertweet-base-sentiment-analysis',
'ahmedrachid/FinancialBERT-Sentiment-Analysis',
'finiteautomata/beto-sentiment-analysis'
],
)
input_sentences = st.text_area("Sentences", value="", height=200)
data = input_sentences.split('\n')
if st.button("Classify"):
for i in data:
st.write(i)
j = classify(model_name.strip(), i)[0]
sentiment = j['label']
confidence = j['score']
st.write(f"{i} :: Classification - {sentiment} with confidence {confidence}")
st.markdown("Link to the app - [image-to-text-app on 🤗 Spaces](https://huggingface.co/spaces/Amrrs/image-to-text-app)")
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