import gradio as gr import torch import os from faster_whisper import WhisperModel from moviepy.video.io.VideoFileClip import VideoFileClip import logging import google.generativeai as genai # Suppress moviepy logs logging.getLogger("moviepy").setLevel(logging.ERROR) # Configure Gemini API genai.configure(api_key=os.environ["GEMINI_API_KEY"]) # Create the Gemini model generation_config = { "temperature": 1, "top_p": 0.95, "top_k": 40, "max_output_tokens": 8192, "response_mime_type": "text/plain", } model = genai.GenerativeModel( model_name="gemini-2.0-flash-exp", generation_config=generation_config, ) # Define the Whisper model and device MODEL_NAME = "Systran/faster-whisper-large-v3" device = "cuda" if torch.cuda.is_available() else "cpu" compute_type = "float32" if device == "cuda" else "int8" # Load the Whisper model whisper_model = WhisperModel(MODEL_NAME, device=device, compute_type=compute_type) # List of all supported languages in Whisper SUPPORTED_LANGUAGES = [ "Auto Detect", "English", "Chinese", "German", "Spanish", "Russian", "Korean", "French", "Japanese", "Portuguese", "Turkish", "Polish", "Catalan", "Dutch", "Arabic", "Swedish", "Italian", "Indonesian", "Hindi", "Finnish", "Vietnamese", "Hebrew", "Ukrainian", "Greek", "Malay", "Czech", "Romanian", "Danish", "Hungarian", "Tamil", "Norwegian", "Thai", "Urdu", "Croatian", "Bulgarian", "Lithuanian", "Latin", "Maori", "Malayalam", "Welsh", "Slovak", "Telugu", "Persian", "Latvian", "Bengali", "Serbian", "Azerbaijani", "Slovenian", "Kannada", "Estonian", "Macedonian", "Breton", "Basque", "Icelandic", "Armenian", "Nepali", "Mongolian", "Bosnian", "Kazakh", "Albanian", "Swahili", "Galician", "Marathi", "Punjabi", "Sinhala", "Khmer", "Shona", "Yoruba", "Somali", "Afrikaans", "Occitan", "Georgian", "Belarusian", "Tajik", "Sindhi", "Gujarati", "Amharic", "Yiddish", "Lao", "Uzbek", "Faroese", "Haitian Creole", "Pashto", "Turkmen", "Nynorsk", "Maltese", "Sanskrit", "Luxembourgish", "Burmese", "Tibetan", "Tagalog", "Malagasy", "Assamese", "Tatar", "Hawaiian", "Lingala", "Hausa", "Bashkir", "Javanese", "Sundanese" ] def extract_audio_from_video(video_file): """Extract audio from a video file and save it as a WAV file.""" video = VideoFileClip(video_file) audio_file = "extracted_audio.wav" video.audio.write_audiofile(audio_file, fps=16000, logger=None) # Suppress logs return audio_file def generate_subtitles(audio_file, language="Auto Detect"): """Generate subtitles from an audio file using Whisper.""" # Transcribe the audio segments, info = whisper_model.transcribe( audio_file, task="transcribe", language=None if language == "Auto Detect" else language.lower(), word_timestamps=True ) # Generate SRT format subtitles srt_subtitles = "" for i, segment in enumerate(segments, start=1): start_time = segment.start end_time = segment.end text = segment.text.strip() # Format timestamps for SRT start_time_srt = format_timestamp(start_time) end_time_srt = format_timestamp(end_time) # Add to SRT srt_subtitles += f"{i}\n{start_time_srt} --> {end_time_srt}\n{text}\n\n" return srt_subtitles, info.language def format_timestamp(seconds): """Convert seconds to SRT timestamp format (HH:MM:SS,mmm).""" hours = int(seconds // 3600) minutes = int((seconds % 3600) // 60) seconds = seconds % 60 milliseconds = int((seconds - int(seconds)) * 1000) return f"{hours:02}:{minutes:02}:{int(seconds):02},{milliseconds:03}" def translate_srt(srt_text, target_language): """Translate an SRT file while preserving timestamps.""" # Magic prompt for Gemini prompt = f"Translate the following SRT subtitles into {target_language}. Preserve the SRT format (timestamps and structure). Translate only the text after the timestamp. Do not add explanations or extra text.\n\n{srt_text}" # Send the prompt to Gemini response = model.generate_content(prompt) return response.text def process_video(video_file, language="Auto Detect", translate_to=None): """Process a video file to generate and translate subtitles.""" # Extract audio from the video audio_file = extract_audio_from_video(video_file) # Generate subtitles subtitles, detected_language = generate_subtitles(audio_file, language) # Save original subtitles to an SRT file original_srt_file = "original_subtitles.srt" with open(original_srt_file, "w", encoding="utf-8") as f: f.write(subtitles) # Translate subtitles if a target language is provided translated_srt_file = None if translate_to and translate_to != "None": translated_subtitles = translate_srt(subtitles, translate_to) translated_srt_file = "translated_subtitles.srt" with open(translated_srt_file, "w", encoding="utf-8") as f: f.write(translated_subtitles) # Clean up extracted audio file os.remove(audio_file) return original_srt_file, translated_srt_file, detected_language # Define the Gradio interface with gr.Blocks(title="AutoSubGen - AI Video Subtitle Generator") as demo: # Header with gr.Column(): gr.Markdown("# 🎥 AutoSubGen") gr.Markdown("### AI-Powered Video Subtitle Generator") gr.Markdown("Automatically generate and translate subtitles for your videos in **SRT format**. Supports **100+ languages** and **auto-detection**.") # Main content with gr.Tab("Generate Subtitles"): gr.Markdown("### Upload a video file to generate subtitles.") with gr.Row(): video_input = gr.Video(label="Upload Video File", scale=2) language_dropdown = gr.Dropdown( choices=SUPPORTED_LANGUAGES, label="Select Language", value="Auto Detect", scale=1 ) translate_to_dropdown = gr.Dropdown( choices=["None"] + SUPPORTED_LANGUAGES[1:], # Exclude "Auto Detect" label="Translate To", value="None", scale=1 ) generate_button = gr.Button("Generate Subtitles", variant="primary") with gr.Row(): original_subtitle_output = gr.File(label="Download Original Subtitles (SRT)") translated_subtitle_output = gr.File(label="Download Translated Subtitles (SRT)") detected_language_output = gr.Textbox(label="Detected Language") # Link button to function generate_button.click( process_video, inputs=[video_input, language_dropdown, translate_to_dropdown], outputs=[original_subtitle_output, translated_subtitle_output, detected_language_output] ) # Launch the Gradio interface with a public link demo.launch(share=True)