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from diffusers import AudioLDMPipeline
import torch
import gradio as gr
from googletrans import Translator
if torch.cuda.is_available():
device = "cuda"
torch_dtype = torch.float16
else:
device = "cpu"
torch_dtype = torch.float32
print(device)
repo_id = "cvssp/audioldm-m-full"
pipe = AudioLDMPipeline.from_pretrained(repo_id, torch_dtype=torch_dtype)
pipe.unet = torch.compile(pipe.unet)
prompt = "Techno music with a strong, upbeat tempo and high melodic riffs"
def generate_sound(text):
print(text)
text=translate_text(text)
print(text)
audio = pipe(text, num_inference_steps=10, audio_length_in_s=5.0).audios[0]
rate =160000
return rate, audio
def translate_text(text):
translator = Translator()
translated_text=translator.translate(text, src='es',dest="en")
return translated_text.text
demo = gr.Blocks()
with demo:
with gr.Row():
with gr.Column():
text = gr.Textbox(value="Ingrese el texto:")
button = gr.Button(value="Generar")
with gr.Column():
output = gr.Audio()
button.click(generate_sound,text,output)
demo.launch() |