app.py

import streamlit as st
from transformers import pipeline

st.set_page_config(page_title="Generate Your Tweet and Toxicity Analysis",
                   page_icon="![image/png](https://cdn-uploads.huggingface.co/production/uploads/66f6b4f934e277e391ccbf93/F7rRfSUX7xBPfmUzG3Mn5.png)")

st.header("Please writedown the first word of a Tweet")
uploaded_file = st.file_uploader("Select an Image...")

if uploaded_file is not None:
    print(uploaded_file)
    bytes_data = uploaded_file.getvalue()
    with open(uploaded_file.name, "wb") as file:
        file.write(bytes_data)
    st.image(uploaded_file, caption="Uploaded Image",
             use_column_width=True)

    #Stage 1: Image to Text
    st.text('Processing img2text...')
    scenario = img2text(uploaded_file.name)
    st.write(scenario)

    #Stage 2: Text to Story
    st.text('Generating a story...')
    story = text2story(scenario)
    st.write(story)

    #Stage 3: Story to Audio data
    st.text('Generating audio data...')
    audio_data =text2audio(story)

    # Play button
    if st.button("Play Audio"):
        st.audio(audio_data['audio'],
                    format="audio/wav",
                    start_time=0,
                    sample_rate = audio_data['sampling_rate'])