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import whisper
import moviepy.editor as mp
import gradio as gr
# Load Whisper model for audio transcription
model_name = "base"
whisper_model = whisper.load_model(model_name)
def generate_srt(transcription_result):
"""Helper function to convert Whisper's transcription with timestamps to SRT format."""
srt_content = ""
for i, segment in enumerate(transcription_result['segments']):
# Convert start and end times to SRT time format
start = segment['start']
end = segment['end']
start_time = f"{int(start//3600):02}:{int((start%3600)//60):02}:{int(start%60):02},{int((start%1)*1000):03}"
end_time = f"{int(end//3600):02}:{int((end%3600)//60):02}:{int(end%60):02},{int((end%1)*1000):03}"
# Create the SRT entry
srt_content += f"{i+1}\n{start_time} --> {end_time}\n{segment['text'].strip()}\n\n"
return srt_content
def transcribe_and_generate_subtitles(video):
# Step 1: Extract the audio from the video using moviepy
video_clip = mp.VideoFileClip(video)
audio_path = "temp_audio.wav"
video_clip.audio.write_audiofile(audio_path, codec='pcm_s16le')
# Step 2: Transcribe the audio with timestamps using Whisper
transcription_result = whisper_model.transcribe(audio_path, task="transcribe", language="en", verbose=False)
# Step 3: Generate SRT subtitles
srt_content = generate_srt(transcription_result)
# Save SRT file
srt_file = "output_subtitles.srt"
with open(srt_file, "w", encoding="utf-8") as f:
f.write(srt_content)
return transcription_result["text"], srt_file
# Set up Gradio interface
interface = gr.Interface(
fn=transcribe_and_generate_subtitles,
inputs=gr.Video(label="Upload Video File"),
outputs=[
gr.Textbox(label="English Transcription"),
gr.File(label="Subtitle File (SRT)")
],
title="Video Subtitle Generator",
description="Upload a video file, and this will generate a transcription and subtitles in SRT format."
)
# Launch the interface
interface.launch()
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