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