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Update app.py
Browse files
app.py
CHANGED
@@ -5,17 +5,53 @@ from PIL import Image
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import torch
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import os
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import tempfile
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import sys
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import subprocess
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#
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try:
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from gtts import gTTS
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except ImportError:
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st.warning("
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# Simple image-to-text function
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def img2text(image):
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@@ -66,26 +102,6 @@ def text2story(text):
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# If no good ending is found, return as is
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return story_text
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# Updated text-to-audio function using gTTS
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def text2audio(story_text):
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# Create a temporary file
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temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
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temp_filename = temp_file.name
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temp_file.close()
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# Use gTTS to convert text to speech
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tts = gTTS(text=story_text, lang='en', slow=False)
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tts.save(temp_filename)
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# Read the audio file
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with open(temp_filename, 'rb') as audio_file:
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audio_bytes = audio_file.read()
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# Clean up the temporary file
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os.unlink(temp_filename)
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return audio_bytes
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# Basic Streamlit interface
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st.title("Image to Audio Story")
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uploaded_file = st.file_uploader("Upload an image")
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# Text to Audio
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with st.spinner("Generating audio..."):
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try:
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# Play audio
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except Exception as e:
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st.error(f"Error generating or playing audio: {e}")
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st.info("
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# Fallback to a simple TTS if gTTS fails
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try:
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st.write("Attempting fallback to pyttsx3...")
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import pyttsx3
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engine = pyttsx3.init()
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# Create a temporary file for the fallback audio
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temp_wav = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
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temp_wav_filename = temp_wav.name
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temp_wav.close()
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# Generate and save speech
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engine.save_to_file(story, temp_wav_filename)
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engine.runAndWait()
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# Read the audio file
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with open(temp_wav_filename, 'rb') as audio_file:
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fallback_audio = audio_file.read()
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# Clean up
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os.unlink(temp_wav_filename)
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st.audio(fallback_audio, format='audio/wav')
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except:
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st.error("Both TTS methods failed. Please install gTTS manually.")
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import torch
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import os
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import tempfile
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# For TTS, try multiple options in order of preference
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try:
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# Try gTTS first
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from gtts import gTTS
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def text2audio(story_text):
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# Create a temporary file
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temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
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temp_filename = temp_file.name
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temp_file.close()
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# Use gTTS to convert text to speech
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tts = gTTS(text=story_text, lang='en', slow=False)
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tts.save(temp_filename)
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# Read the audio file
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with open(temp_filename, 'rb') as audio_file:
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audio_bytes = audio_file.read()
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# Clean up the temporary file
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os.unlink(temp_filename)
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return audio_bytes, 'audio/mp3'
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except ImportError:
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st.warning("gTTS not available. Using alternative text-to-speech method.")
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# Define alternative TTS using built-in transformers pipeline
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def text2audio(story_text):
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# Use a different TTS method
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from transformers import pipeline
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# Try a simple TTS model that should work with base transformers
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synthesizer = pipeline("text-to-speech", model="facebook/mms-tts-eng")
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# Generate speech
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speech = synthesizer(story_text)
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# Return the audio data
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if 'audio' in speech:
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return speech['audio'], speech.get('sampling_rate', 16000)
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elif 'audio_array' in speech:
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return speech['audio_array'], speech.get('sampling_rate', 16000)
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else:
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# In case of failure, return an error message
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raise Exception("Failed to generate audio with any available method")
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# Simple image-to-text function
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def img2text(image):
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# If no good ending is found, return as is
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return story_text
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# Basic Streamlit interface
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st.title("Image to Audio Story")
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uploaded_file = st.file_uploader("Upload an image")
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# Text to Audio
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with st.spinner("Generating audio..."):
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try:
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audio_data, audio_format = text2audio(story)
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# Play audio
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if isinstance(audio_format, str) and audio_format.startswith('audio/'):
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st.audio(audio_data, format=audio_format)
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else:
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st.audio(audio_data, sample_rate=audio_format)
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except Exception as e:
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st.error(f"Error generating or playing audio: {e}")
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st.info("There was an issue with the text-to-speech conversion.")
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