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import re |
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import streamlit as st |
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from transformers import pipeline |
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import textwrap |
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import numpy as np |
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import soundfile as sf |
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import tempfile |
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import os |
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from PIL import Image |
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import string |
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@st.cache_resource |
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def load_pipelines(): |
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captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large") |
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storyer = pipeline("text-generation", model="aspis/gpt2-genre-story-generation") |
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tts = pipeline("text-to-speech", model="facebook/mms-tts-eng") |
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return captioner, storyer, tts |
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captioner, storyer, tts = load_pipelines() |
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def clean_generated_story(raw_story: str) -> str: |
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""" |
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Cleans the generated story by: |
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1. Removing URLs. |
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2. Removing digits. |
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3. Removing words likely to be random letter combinations based on having no vowels. |
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4. Removing single-letter words unless allowed (such as 'a' or 'I'). |
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""" |
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no_urls = re.sub(r'\b(?:https?://|www\.)\S+\b', '', raw_story) |
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no_urls = re.sub(r'\b\w+\.(com|net|org|co\.uk|ca\.us|me)\b', '', no_urls) |
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story_without_numbers = re.sub(r'\d+', '', no_urls) |
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vowels = set('aeiouAEIOU') |
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def is_valid_word(word: str) -> bool: |
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if len(word) == 1 and word.lower() not in ['a', 'i']: |
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return False |
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if len(word) > 1 and not any(char in vowels for char in word): |
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return False |
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return True |
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words = story_without_numbers.split() |
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filtered_words = [word for word in words if is_valid_word(word)] |
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clean_story = " ".join(filtered_words[:100]) |
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return clean_story |
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def get_caption(image) -> str: |
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""" |
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Takes an image and returns a generated caption. |
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""" |
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pil_image = Image.open(image) |
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caption = captioner(pil_image)[0]["generated_text"] |
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st.write("**๐ What's in the picture: ๐**") |
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st.write(caption) |
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return caption |
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def get_story(caption: str) -> str: |
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""" |
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Takes a caption and returns a funny, bright, and playful story targeted toward young children. |
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""" |
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prompt = ( |
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f"Write a funny and playful story for young children precisely centered on this scene {caption}\nStory: " |
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f"mention the exact place, location or venue within {caption}. " |
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f"Make the story magical and exciting." |
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) |
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raw = storyer( |
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prompt, |
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max_new_tokens=150, |
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temperature=0.7, |
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top_p=0.9, |
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no_repeat_ngram_size=2, |
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return_full_text=False |
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)[0]["generated_text"].strip() |
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story = clean_generated_story(raw) |
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st.write("**๐ Your funny story: ๐**") |
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st.write(story) |
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return story |
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def generate_audio(story: str) -> str: |
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""" |
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Converts the text story into speech audio and returns the file path for the audio. |
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""" |
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chunks = textwrap.wrap(story, width=200) |
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audio = np.concatenate([tts(chunk)["audio"].squeeze() for chunk in chunks]) |
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with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file: |
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sf.write(temp_file.name, audio, tts.model.config.sampling_rate) |
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temp_file_path = temp_file.name |
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return temp_file_path |
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def generate_content(image): |
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""" |
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Pipeline function that: |
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- Generates a caption from the uploaded image. |
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- Uses the caption to generate a story. |
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- Converts the story to speech audio. |
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""" |
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caption = get_caption(image) |
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story = get_story(caption) |
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audio_path = generate_audio(story) |
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return caption, story, audio_path |
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st.title("โจ Magic Story Maker โจ") |
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st.markdown("Upload a picture to make a funny story and hear it too! ๐ธ") |
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uploaded_image = st.file_uploader("Choose your picture", type=["jpg", "jpeg", "png"]) |
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if uploaded_image is None: |
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st.image("https://example.com/placeholder_image.jpg", caption="Upload your picture here! ๐ท", use_container_width=True) |
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else: |
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st.image(uploaded_image, caption="Your Picture ๐", use_container_width=True) |
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if st.button("โจ Make My Story! โจ"): |
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if uploaded_image is not None: |
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with st.spinner("๐ฎ Creating your magical story..."): |
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caption, story, audio_path = generate_content(uploaded_image) |
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st.success("๐ Your story is ready! ๐") |
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st.audio(audio_path, format="audio/wav") |
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os.remove(audio_path) |
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else: |
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st.warning("Please upload a picture first! ๐ธ") |