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import whisper
import moviepy.editor as mp
import gradio as gr
import torch
import subprocess
# 1. Load Whisper Model and Move to GPU if Available
device = "cuda" if torch.cuda.is_available() else "cpu"
model_name = "tiny" # Use 'tiny' model for faster processing, change to 'base' or larger for more accuracy
whisper_model = whisper.load_model(model_name).to(device)
# Helper function to convert Whisper's transcription to SRT format
def generate_srt(transcription_result):
"""Convert transcription with timestamps to SRT format."""
srt_content = ""
for i, segment in enumerate(transcription_result['segments']):
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}"
srt_content += f"{i+1}\n{start_time} --> {end_time}\n{segment['text'].strip()}\n\n"
return srt_content
# 2. Function to Extract Audio using optimized FFmpeg subprocess
def extract_audio_ffmpeg(video_file, audio_output):
"""Extract audio using ffmpeg with optimized settings."""
subprocess.run([
'ffmpeg', '-i', video_file, '-vn', '-acodec', 'pcm_s16le', '-ar', '16000', audio_output, '-y'
])
# 3. Function to Transcribe, Translate (if necessary), and Generate Subtitles
def transcribe_and_generate_subtitles(video):
# Step 1: Extract audio from video using optimized FFmpeg
audio_path = "temp_audio.wav"
extract_audio_ffmpeg(video, audio_path)
# Step 2: Transcribe the audio
transcription_result = whisper_model.transcribe(audio_path, language="en", verbose=False)
# Step 3: Detect language and translate if necessary
detected_language = transcription_result['language']
if detected_language == "hau": # Assuming "hau" is the code for Hausa
# Re-transcribe with translation to English
transcription_result = whisper_model.transcribe(audio_path, task="translate", verbose=False)
# Step 4: 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)
# Step 5: Add subtitles to the video
output_video = "video_with_subtitles.mp4"
subprocess.run([
'ffmpeg', '-i', video, '-vf', f"subtitles={srt_file}", output_video, '-y'
])
return transcription_result["text"], output_video
# 4. Set up Gradio Interface with Optimized Settings
interface = gr.Interface(
fn=transcribe_and_generate_subtitles,
inputs=gr.Video(label="Upload Video File"),
outputs=[
gr.Textbox(label="Transcription or Translation"),
gr.File(label="Download Video with Subtitles")
],
title="Video Subtitle Generator",
description="Upload a video in either English or Hausa. The system will detect the language, transcribe or translate if necessary, and generate a video with subtitles embedded.",
live=False # Disable live updates for faster processing
)
# Launch the interface
interface.launch()
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