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import gradio as gr
import moviepy.editor as mp
from transformers import pipeline
# Load Whisper model for speech-to-text
asr = pipeline("automatic-speech-recognition", model="openai/whisper-large")
# MarianMT or M2M100 for translation (multi-language)
translator = pipeline("translation", model="facebook/m2m100_418M")
def generate_subtitles(video_path, target_language):
# Extract audio from video
video = mp.VideoFileClip(video_path)
audio = video.audio
audio.write_audiofile("temp_audio.wav", codec='pcm_s16le')
# Convert speech to text (ASR using Whisper)
with open("temp_audio.wav", "rb") as audio_file:
transcription = asr(audio_file)["text"]
# Translate transcription to the target language using M2M100
translation_pipeline = pipeline('translation', model='facebook/m2m100_418M')
translated_subtitles = translation_pipeline(
transcription,
forced_bos_token_id=translation_pipeline.tokenizer.get_lang_id(target_language)
)[0]["translation_text"]
# Return subtitles (text for now)
subtitles = f"Original: {transcription}\nTranslated: {translated_subtitles}"
return subtitles
# Define Gradio interface
def subtitle_video(video_file, target_language):
video_path = video_file.name
return generate_subtitles(video_path, target_language)
# List of supported languages with their codes for M2M100
languages = {
"Persian (fa)": "fa",
"French (fr)": "fr",
"Spanish (es)": "es",
"German (de)": "de",
"Chinese (zh)": "zh",
"Arabic (ar)": "ar",
"Hindi (hi)": "hi",
"Russian (ru)": "ru"
}
# Gradio app layout
interface = gr.Interface(
fn=subtitle_video,
inputs=[
gr.Video(label="Upload Video"),
gr.Dropdown( # Dropdown for language selection
label="Choose Target Language",
choices=list(languages.keys()), # Display language names in the dropdown
value="Persian (fa)" # Default language
)
],
outputs="text",
title="Automatic Video Subtitler & Translator"
)
interface.launch()
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