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import streamlit as st | |
from transformers import pipeline | |
def img2text(url): | |
image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large", use_fast=True) | |
text = image_to_text_model(url)[0]["generated_text"] | |
return text | |
def text2story(text): | |
story_generator = pipeline("text-generation", model="pranavpsv/gpt2-genre-story-generator", device_map="auto", return_full_text=False) | |
prompt = f"<BOS> {text}" | |
generated = story_generator(prompt, max_new_tokens=140, do_sample=True, temperature=0.7) | |
story_text = generated[0]['generated_text'] | |
# Split into sentences | |
sentences = re.split(r'(?<=[.!?])\s+', story_text.strip()) | |
# Initialize variables | |
current_word_count = 0 | |
final_sentences = [] | |
# Iterate through each sentence and accumulate until the word count is within 100 | |
for sentence in sentences: | |
words = sentence.split() | |
word_count = len(words) | |
if current_word_count + word_count > 100: | |
break | |
final_sentences.append(sentence) | |
current_word_count += word_count | |
# Join the final sentences to form the story | |
final_story = ' '.join(final_sentences) | |
# Ensure it ends with a punctuation mark | |
if not final_story.endswith(('.', '!', '?')): | |
final_story += '.' | |
return final_story | |
def text2audio(story_text): | |
audio_generator = pipeline("text-to-speech", model="ylacombe/vits_vctk_scottish_female") | |
audio_output = audio_generator(story_text) | |
return audio_output | |
st.set_page_config(page_title="Once Upon A Time - Storytelling Application", page_icon="π") | |
st.header("Create a story of yours with an image!π§") | |
uploaded_file = st.file_uploader("Upload an image for creating your story!") | |
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_container_width=True) | |
st.text('Entering the scene...π°') | |
scenario = img2text(uploaded_file.name) | |
st.write(scenario) | |
st.text('Your story is going to begin...π¦') | |
story = text2story(scenario) | |
st.write(story) | |
audio_data = text2audio(story) | |
st.audio(audio_data['audio'], format="audio/wav", start_time=0, sample_rate = audio_data['sampling_rate']) |