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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) |