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import gradio as gr |
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import torchaudio |
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import torchaudio.transforms as T |
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from transformers import pipeline |
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import requests |
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from pydub import AudioSegment |
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from pydub.silence import split_on_silence |
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import io |
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import os |
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from bs4 import BeautifulSoup |
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import re |
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import numpy as np |
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from moviepy.editor import VideoFileClip |
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import soundfile as sf |
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from spellchecker import SpellChecker |
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import tempfile |
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transcription_pipeline = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h") |
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spell = SpellChecker() |
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def download_audio_from_url(url): |
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try: |
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if "share" in url: |
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print("Processing shareable link...") |
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response = requests.get(url) |
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soup = BeautifulSoup(response.content, 'html.parser') |
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video_tag = soup.find('video') |
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if video_tag and 'src' in video_tag.attrs: |
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video_url = video_tag['src'] |
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print(f"Extracted video URL: {video_url}") |
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else: |
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raise ValueError("Direct video URL not found in the shareable link.") |
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else: |
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video_url = url |
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print(f"Downloading video from URL: {video_url}") |
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response = requests.get(video_url) |
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audio_bytes = response.content |
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print(f"Successfully downloaded {len(audio_bytes)} bytes of data") |
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return audio_bytes |
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except Exception as e: |
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print(f"Error in download_audio_from_url: {str(e)}") |
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raise |
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def correct_spelling(text): |
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words = text.split() |
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corrected_words = [spell.correction(word) or word for word in words] |
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return ' '.join(corrected_words) |
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def format_transcript(transcript): |
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sentences = transcript.split('.') |
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formatted_transcript = [] |
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current_speaker = None |
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for sentence in sentences: |
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if ':' in sentence: |
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speaker, content = sentence.split(':', 1) |
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if speaker != current_speaker: |
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formatted_transcript.append(f"\n\n{speaker.strip()}:{content.strip()}.") |
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current_speaker = speaker |
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else: |
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formatted_transcript.append(f"{content.strip()}.") |
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else: |
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formatted_transcript.append(sentence.strip() + '.') |
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return ' '.join(formatted_transcript) |
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def transcribe_audio(video_bytes): |
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try: |
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with open("temp_video.mp4", "wb") as f: |
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f.write(video_bytes) |
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video = VideoFileClip("temp_video.mp4") |
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audio = video.audio |
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audio.write_audiofile("temp_audio.wav", fps=16000, nbytes=2, codec='pcm_s16le') |
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audio_data, sample_rate = sf.read("temp_audio.wav") |
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if len(audio_data.shape) > 1: |
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audio_data = audio_data.mean(axis=1) |
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audio_data = audio_data.astype(np.float32) / np.max(np.abs(audio_data)) |
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result = transcription_pipeline(audio_data) |
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transcript = result['text'] |
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transcript = correct_spelling(transcript) |
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transcript = format_transcript(transcript) |
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os.remove("temp_video.mp4") |
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os.remove("temp_audio.wav") |
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return transcript |
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except Exception as e: |
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print(f"Error in transcribe_audio: {str(e)}") |
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raise |
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def transcribe_video(url): |
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try: |
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print(f"Attempting to download audio from URL: {url}") |
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audio_bytes = download_audio_from_url(url) |
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print(f"Successfully downloaded {len(audio_bytes)} bytes of audio data") |
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print("Starting audio transcription...") |
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transcript = transcribe_audio(audio_bytes) |
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print("Transcription completed successfully") |
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return transcript |
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except Exception as e: |
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error_message = f"An error occurred: {str(e)}" |
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print(error_message) |
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return error_message |
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def download_transcript(transcript): |
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with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.txt') as temp_file: |
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temp_file.write(transcript) |
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temp_file_path = temp_file.name |
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return temp_file_path |
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with gr.Blocks(title="Video Transcription") as demo: |
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gr.Markdown("# Video Transcription") |
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video_url = gr.Textbox(label="Video URL") |
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transcribe_button = gr.Button("Transcribe") |
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transcript_output = gr.Textbox(label="Transcript", lines=20) |
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download_button = gr.Button("Download Transcript") |
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download_link = gr.File(label="Download Transcript") |
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transcribe_button.click(fn=transcribe_video, inputs=video_url, outputs=transcript_output) |
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download_button.click(fn=download_transcript, inputs=transcript_output, outputs=download_link) |
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demo.launch() |