Spaces:
Runtime error
Runtime error
import streamlit as st | |
from transformers import pipeline | |
st.set_page_config(page_title="Your Image to Audio Story", | |
page_icon="🦜") | |
st.header("Turn Your Image to Audio Story") | |
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) | |
#Define function: | |
def img2txt(imgname): | |
pipe = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning") | |
scenario = pipe(imgname) | |
return scenario[0]['generated_text'] | |
def txt2story(txtname): | |
pipe = pipeline("text-generation", model="openai-community/gpt2") | |
story = pipe(txtname) | |
return story[0]["generated_text"] | |
def text2audio(textname): | |
pipe = pipeline("text-to-speech", model="facebook/mms-tts-eng") | |
audio_data = pipe(textname) | |
return audio_data | |
#Stage 1: Image to Text | |
st.text('Processing img2text...') | |
scenario = img2txt(uploaded_file.name) | |
st.write(scenario) | |
#Stage 2: Text to Story | |
st.text('Generating a story...') | |
story = txt2story(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']) |