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| import streamlit as st | |
| from PIL import Image | |
| from transformers import pipeline | |
| from langchain_openai import ChatOpenAI | |
| import wave | |
| import numpy as np | |
| from langchain_core.prompts import ChatPromptTemplate | |
| from langchain_core.output_parsers import StrOutputParser | |
| openai_key = st.sidebar.text_input("Enter your OpenAI Key", type="password") | |
| # Use a pipeline as a high-level helper | |
| pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") | |
| pipe2 = pipeline("text-to-speech", model="facebook/mms-tts-eng") | |
| output_parser = StrOutputParser() | |
| def get_scenario_from_img_text(text): | |
| llm = ChatOpenAI(openai_api_key=openai_key) | |
| prompt = ChatPromptTemplate.from_messages([ | |
| ("system", "You need to write few lines on the scenario provided by user."), | |
| ("user", "{text}") | |
| ]) | |
| chain = prompt | llm | |
| response = chain.invoke({"text": text}) | |
| return response.content | |
| def main(): | |
| st.title("Image-to-Text-to-Speech App") | |
| # Upload image file | |
| uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file is not None: | |
| # Open and display the uploaded image | |
| img = Image.open(uploaded_file) | |
| st.image(img, caption="Uploaded Image", use_column_width=True) | |
| # Generate text from the image | |
| result = pipe(img) | |
| text = result[0]['generated_text'] | |
| print(text) | |
| text = get_scenario_from_img_text(text) | |
| print(text) | |
| speech = speech = pipe2(text) | |
| # Display the generated text | |
| st.subheader("Generated Text:") | |
| st.write(text) | |
| wav_data = np.array(speech['audio'] * 32767, dtype=np.int16) | |
| with wave.open('output.wav', 'wb') as wav_file: | |
| wav_file.setnchannels(1) | |
| wav_file.setsampwidth(wav_data.dtype.itemsize) | |
| wav_file.setframerate(speech['sampling_rate']) | |
| wav_file.writeframes(wav_data.tobytes()) | |
| # Play the WAV file using the st.audio() function | |
| st.audio('output.wav') | |
| if __name__ == "__main__": | |
| main() |