Update app.py

app.py

@@ -1,87 +1,24 @@
-import subprocess
-import os
+import gradio as gr
 import torch
-import urllib.request
-import librosa
-from moviepy.editor import VideoFileClip
+import os
+import zipfile
+import requests
 from TTS.api import TTS
-
-# Check if PyTorch is using the GPU for computations
-if torch.cuda.is_available():
- device = torch.device("cuda")
- print("Using the GPU for computations")
-else:
- device = torch.device("cpu")
- print("Using the CPU for computations")
-
 os.environ["COQUI_TOS_AGREED"] = "1"
-
+device = "cuda"
 tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
 
-def convert_audio_to_wav(file_path):
- """Convert the given audio file to WAV format."""
- file_name = os.path.basename(file_path)
- file_ext = os.path.splitext(file_name)[1].lower()
-
- if file_ext == ".mp3":
- audio, sr = librosa.load(file_path)
- librosa.output.write_wav(f"temp_{file_name}", audio, sr)
- file_path = f"temp_{file_name}"
- elif file_ext == ".flac":
- os.system(f"ffmpeg -i {file_path} -acodec pcm_s16le -ar 16000 temp_{file_name}")
- file_path = f"temp_{file_name}"
- elif file_ext == ".mp4":
- clip = VideoFileClip(file_path, audio_codec="aac")
- audio = clip.audio
- audio.write_audiofile(f"temp_{file_name}")
- file_path = f"temp_{file_name}"
-
- return file_path
-
 def clone(text, url, language):
- """Generate a voice clone using the given parameters."""
  response = requests.get(url)
-
  with open("temp.zip", "wb") as f:
  f.write(response.content)
-
  with zipfile.ZipFile("temp.zip", "r") as zip_ref:
  zip_ref.extractall()
-
  audio_file = [f for f in os.listdir(".") if f.endswith(".wav")][0]
-
- # Convert the audio file to WAV format
- if os.path.splitext(audio_file)[1].lower() not in [".wav", ".flac"]:
- audio_file = convert_audio_to_wav(audio_file)
-
- # Check if a GPU is available
- if torch.cuda.is_available():
- # Set the device to the GPU
- device = torch.device("cuda")
- print("Using the GPU for computations")
- else:
- # Set the device to the CPU
- device = torch.device("cpu")
- print("Using the CPU for computations")
-
- # Load the TTS model and move it to the device
- tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
-
  tts.tts_to_file(text=text, speaker_wav=audio_file, language=language, file_path="./output.wav")
-
  os.remove(audio_file)
  os.remove("temp.zip")
-
  return "./output.wav"
 
-iface = gr.Interface(fn=clone,
- inputs=["text", gr.components.Text(label="URL"), gr.Dropdown(choices=["en", "es", "fr", "de", "it", "pt", "pl", "tr", "ru", "nl", "cs", "ar", "zh-cn", "ja", "hu", "ko", "hi"], label="Language")],
- outputs=gr.Audio(type='filepath'),
- title='Voice Clone',
- description="""
- by [Angetyde](https://youtube.com/@Angetyde?si=7nusP31nTumIkPTF) and$@$v=v1.16$@$[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"))
-
+iface = gr.Interface(fn=clone, inputs=["text", gr.components.Text(label="URL"), gr.Dropdown(choices=["en", "es", "fr", "de", "it", "ja", "zh-CN", "zh-TW"], label="Language")], outputs=gr.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"))
 iface.launch(share=True)