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Create abc.txt

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  1. abc.txt +177 -0
abc.txt ADDED
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+ import streamlit as st
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+ import moviepy.editor as mp
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+ import speech_recognition as sr
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+ from pydub import AudioSegment
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+ import tempfile
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+ import os
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+ import io
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+
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+ # Function to convert video to audio
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+ def video_to_audio(video_file):
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+ # Load the video using moviepy
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+ video = mp.VideoFileClip(video_file)
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+
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+ # Extract audio
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+ audio = video.audio
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+ temp_audio_path = tempfile.mktemp(suffix=".mp3")
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+
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+ # Write the audio to a file
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+ audio.write_audiofile(temp_audio_path)
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+ return temp_audio_path
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+
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+ # Function to convert MP3 audio to WAV
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+ def convert_mp3_to_wav(mp3_file):
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+ # Load the MP3 file using pydub
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+ audio = AudioSegment.from_mp3(mp3_file)
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+
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+ # Create a temporary WAV file
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+ temp_wav_path = tempfile.mktemp(suffix=".wav")
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+
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+ # Export the audio to the temporary WAV file
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+ audio.export(temp_wav_path, format="wav")
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+ return temp_wav_path
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+
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+ # Function to transcribe audio to text
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+ def transcribe_audio(audio_file):
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+ # Initialize recognizer
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+ recognizer = sr.Recognizer()
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+
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+ # Load the audio file using speech_recognition
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+ audio = sr.AudioFile(audio_file)
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+
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+ with audio as source:
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+ audio_data = recognizer.record(source)
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+
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+ try:
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+ # Transcribe the audio data to text using Google Web Speech API
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+ text = recognizer.recognize_google(audio_data)
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+ return text
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+ except sr.UnknownValueError:
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+ return "Audio could not be understood."
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+ except sr.RequestError:
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+ return "Could not request results from Google Speech Recognition service."
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+
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+ # Streamlit app layout
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+ st.title("Video and Audio to Text Transcription")
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+ st.write("Upload a video or audio file to convert it to transcription.")
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+
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+ # Create tabs to separate video and audio uploads
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+ tab = st.selectbox("Select the type of file to upload", ["Video", "Audio"])
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+
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+ if tab == "Video":
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+ # File uploader for video
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+ uploaded_video = st.file_uploader("Upload Video", type=["mp4", "mov", "avi"])
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+
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+ if uploaded_video is not None:
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+ # Save the uploaded video file temporarily
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+ with tempfile.NamedTemporaryFile(delete=False) as tmp_video:
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+ tmp_video.write(uploaded_video.read())
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+ tmp_video_path = tmp_video.name
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+
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+ # Add an "Analyze Video" button
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+ if st.button("Analyze Video"):
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+ with st.spinner("Processing video... Please wait."):
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+ # Convert video to audio
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+ audio_file = video_to_audio(tmp_video_path)
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+
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+ # Convert the extracted MP3 audio to WAV
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+ wav_audio_file = convert_mp3_to_wav(audio_file)
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+
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+ # Transcribe audio to text
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+ transcription = transcribe_audio(wav_audio_file)
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+
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+ # Show the transcription
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+ st.text_area("Transcription", transcription, height=300)
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+
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+ # Store transcription and audio file in session state
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+ st.session_state.transcription = transcription
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+
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+ # Store the audio file as a BytesIO object in memory
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+ with open(wav_audio_file, "rb") as f:
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+ audio_data = f.read()
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+ st.session_state.wav_audio_file = io.BytesIO(audio_data)
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+
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+ # Cleanup temporary files
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+ os.remove(tmp_video_path)
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+ os.remove(audio_file)
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+
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+ # Check if transcription and audio file are stored in session state
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+ if 'transcription' in st.session_state and 'wav_audio_file' in st.session_state:
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+ # Provide the audio file to the user for download
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+ st.audio(st.session_state.wav_audio_file, format='audio/wav')
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+
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+ # Add download buttons for the transcription and audio
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+ # Downloadable transcription file
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+ st.download_button(
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+ label="Download Transcription",
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+ data=st.session_state.transcription,
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+ file_name="transcription.txt",
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+ mime="text/plain"
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+ )
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+
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+ # Downloadable audio file
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+ st.download_button(
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+ label="Download Audio",
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+ data=st.session_state.wav_audio_file,
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+ file_name="converted_audio.wav",
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+ mime="audio/wav"
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+ )
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+
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+ elif tab == "Audio":
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+ # File uploader for audio
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+ uploaded_audio = st.file_uploader("Upload Audio", type=["wav", "mp3"])
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+
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+ if uploaded_audio is not None:
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+ # Save the uploaded audio file temporarily
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+ with tempfile.NamedTemporaryFile(delete=False) as tmp_audio:
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+ tmp_audio.write(uploaded_audio.read())
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+ tmp_audio_path = tmp_audio.name
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+
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+ # Add an "Analyze Audio" button
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+ if st.button("Analyze Audio"):
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+ with st.spinner("Processing audio... Please wait."):
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+ # Convert audio to WAV if it's in MP3 format
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+ if uploaded_audio.type == "audio/mpeg":
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+ wav_audio_file = convert_mp3_to_wav(tmp_audio_path)
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+ else:
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+ wav_audio_file = tmp_audio_path
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+
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+ # Transcribe audio to text
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+ transcription = transcribe_audio(wav_audio_file)
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+
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+ # Show the transcription
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+ st.text_area("Transcription", transcription, height=300)
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+
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+ # Store transcription in session state
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+ st.session_state.transcription_audio = transcription
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+
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+ # Store the audio file as a BytesIO object in memory
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+ with open(wav_audio_file, "rb") as f:
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+ audio_data = f.read()
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+ st.session_state.wav_audio_file_audio = io.BytesIO(audio_data)
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+
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+ # Cleanup temporary audio file
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+ os.remove(tmp_audio_path)
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+
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+ # Check if transcription and audio file are stored in session state
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+ if 'transcription_audio' in st.session_state and 'wav_audio_file_audio' in st.session_state:
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+ # Provide the audio file to the user for download
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+ st.audio(st.session_state.wav_audio_file_audio, format='audio/wav')
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+
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+ # Add download buttons for the transcription and audio
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+ # Downloadable transcription file
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+ st.download_button(
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+ label="Download Transcription",
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+ data=st.session_state.transcription_audio,
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+ file_name="transcription_audio.txt",
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+ mime="text/plain"
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+ )
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+
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+ # Downloadable audio file
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+ st.download_button(
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+ label="Download Audio",
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+ data=st.session_state.wav_audio_file_audio,
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+ file_name="converted_audio_audio.wav",
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+ mime="audio/wav"
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+ )
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+