import streamlit as st import moviepy.editor as mp import speech_recognition as sr from pydub import AudioSegment import tempfile import os import io import requests import execjs import re import json # 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." # Function to get HTML content for extracting video URL def gethtml(url): headers = { "cache-Control": "no-cache", "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9", "accept-encoding": "gzip, deflate, br", "accept-language": "zh-CN,zh;q=0.9,en;q=0.8", "content-type": "application/x-www-form-urlencoded", "cookie": "lang=en; country=CN; uid=fd94a82a406a8dd4; sfHelperDist=72; reference=14;", "origin": "https://en.savefrom.net", "referer": "https://en.savefrom.net/1-youtube-video-downloader-4/", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36" } kv = {"sf_url": url, "sf_submit": "", "new": "1", "lang": "en", "app": "", "country": "cn", "os": "Windows", "browser": "Chrome"} r = requests.post(url="https://en.savefrom.net/savefrom.php", headers=headers, data=kv) r.raise_for_status() return r.text # Function to extract the video download URL def extract_video_url(youtube_url): reo = gethtml(youtube_url) reo = reo.split("")[0] reo = reo.replace("(function(){", "(function(){\nthis.alert=function(){};") reA = reo.split("\n") name = reA[len(reA) - 3].split(";")[0] + ";" addition = """ const jsdom = require("jsdom"); const { JSDOM } = jsdom; const dom = new JSDOM(`

Hello world

`); window = dom.window; document = window.document; XMLHttpRequest = window.XMLHttpRequest; """ ct = execjs.compile(addition + reo, cwd=r'C:\Users\19308\AppData\Roaming\npm\node_modules') text = ct.eval(name.split("=")[1].replace(";", "")) result = re.search('show\((.*?)\);;', text, re.I | re.M).group(0).replace("show(", "").replace(");;", "") j = json.loads(result) num = 1 downurl = j["url"][num]["url"] return downurl # Streamlit app layout st.title("Video and Audio to Text Transcription") st.write("Upload a video or audio file to convert it to transcription, or enter a YouTube URL to download the video.") # Create tabs to separate video, audio, and YouTube download options tab = st.selectbox("Select the type of file to upload or download", ["Video", "Audio", "YouTube"]) 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" ) elif tab == "YouTube": youtube_url = st.text_input("Enter YouTube Video URL", "https://www.youtube.com/watch?v=YPvtz1lHRiw") if st.button("Get Download Link"): if youtube_url: try: download_url = extract_video_url(youtube_url) st.success("Download link generated successfully!") st.write("Click below to download the video:") st.markdown(f"[Download Video]({download_url})", unsafe_allow_html=True) except Exception as e: st.error(f"Error occurred: {e}") else: st.error("Please enter a valid YouTube URL.")