import gradio as gr import torch import os import zipfile import requests from TTS.api import TTS from pydub import AudioSegment # Set environment variable os.environ["COQUI_TOS_AGREED"] = "1" # Define constants MODEL_PATH = "tts_models/multilingual/multi-dataset/xtts_v2" LANGUAGES = ["en", "es", "fr", "de", "it", "pt", "pl", "tr", "ru", "nl", "cs", "ar", "zh-cn", "ja", "hu", "ko", "hi"] AUDIO_FORMATS = [".wav", ".mp3", ".flac", ".mp4"] # Automatically detect and use GPU if available device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") print(f"Using device: {device}") # Load TTS model tts = TTS(MODEL_PATH).to(device) def convert_to_wav(audio_file): # Extract file extension file_extension = os.path.splitext(audio_file)[-1].lower() # Convert audio file to.wav format if file_extension!= ".wav": audio = AudioSegment.from_file(audio_file) audio.export("temp.wav", format="wav") os.remove(audio_file) audio_file = "temp.wav" return audio_file def clone(text, audio_or_url, language): # Check if audio_or_url is a file object or a string if isinstance(audio_or_url, str): # Download audio file from URL response = requests.get(audio_or_url) with open("temp.wav", "wb") as f: f.write(response.content) audio_file = "temp.wav" else: # Save uploaded audio file to a temporary location audio_file = "temp.wav" with open(audio_file, "wb") as f: f.write(audio_or_url.read()) # Convert audio file to.wav format audio_file = convert_to_wav(audio_file) # Generate audio using TTS model tts.tts_to_file(text=text, speaker_wav=audio_file, language=language, file_path="./output.wav") # Clean up os.remove(audio_file) return "./output.wav" # Create Gradio interface iface = gr.Interface( fn=clone, inputs=["text", gr.Audio(label="Upload audio file or enter URL"), gr.Dropdown(choices=LANGUAGES, label="Language")], outputs=gr.outputs.Audio(type="filepath"), title="Voice Clone", description=""" by [Angetyde](https://youtube.com/@Angetyde?si=7nusP31nTumIkPTF) and [Tony Assi](https://www.tonyassi.com/ ) use this colab with caution <3. """, theme=gr.themes.Base(primary_hue="teal", secondary_hue="teal", neutral_hue="slate") ) # Launch Gradio interface iface.launch(share=True)