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)")