Spaces:
Runtime error
Runtime error
File size: 4,916 Bytes
3d41f57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
import torch
import torchaudio
from einops import rearrange
from stable_audio_tools import get_pretrained_model
from stable_audio_tools.inference.generation import generate_diffusion_cond
from pydub import AudioSegment
import re
import os
from datetime import datetime
import gradio as gr
# Define the function to generate audio based on a prompt
def generate_audio(prompt, steps, cfg_scale, sigma_min, sigma_max, generation_time, seed, sampler_type):
device = "cuda" if torch.cuda.is_available() else "cpu"
# Download model
model, model_config = get_pretrained_model("audo/stable-audio-open-1.0")
sample_rate = model_config["sample_rate"]
sample_size = model_config["sample_size"]
model = model.to(device)
# Set up text and timing conditioning
conditioning = [{
"prompt": prompt,
"seconds_start": 0,
"seconds_total": generation_time
}]
# Generate stereo audio
output = generate_diffusion_cond(
model,
steps=steps,
cfg_scale=cfg_scale,
conditioning=conditioning,
sample_size=sample_size,
sigma_min=sigma_min,
sigma_max=sigma_max,
sampler_type=sampler_type,
device=device,
seed=seed
)
# Rearrange audio batch to a single sequence
output = rearrange(output, "b d n -> d (b n)")
# Peak normalize, clip, convert to int16, and save to temporary file
output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()
torchaudio.save("temp_output.wav", output, sample_rate)
# Convert to MP3 format using pydub
audio = AudioSegment.from_wav("temp_output.wav")
# Create Output folder and dated subfolder if they do not exist
output_folder = "Output"
date_folder = datetime.now().strftime("%Y-%m-%d")
save_path = os.path.join(output_folder, date_folder)
os.makedirs(save_path, exist_ok=True)
# Generate a filename based on the prompt
filename = re.sub(r'\W+', '_', prompt) + ".mp3" # Replace non-alphanumeric characters with underscores
full_path = os.path.join(save_path, filename)
# Ensure the filename is unique by appending a number if the file already exists
base_filename = filename
counter = 1
while os.path.exists(full_path):
filename = f"{base_filename[:-4]}_{counter}.mp3"
full_path = os.path.join(save_path, filename)
counter += 1
# Export the audio to MP3 format
audio.export(full_path, format="mp3")
return full_path
def audio_generator(prompt, sampler_type, steps, cfg_scale, sigma_min, sigma_max, generation_time, seed):
try:
print("Generating audio with parameters:")
print("Prompt:", prompt)
print("Sampler Type:", sampler_type)
print("Steps:", steps)
print("CFG Scale:", cfg_scale)
print("Sigma Min:", sigma_min)
print("Sigma Max:", sigma_max)
print("Generation Time:", generation_time)
print("Seed:", seed)
filename = generate_audio(prompt, steps, cfg_scale, sigma_min, sigma_max, generation_time, seed, sampler_type)
return gr.Audio(filename), f"Generated: {filename}"
except Exception as e:
return str(e)
# Create Gradio interface
prompt_textbox = gr.Textbox(lines=5, label="Prompt")
sampler_dropdown = gr.Dropdown(
label="Sampler Type",
choices=[
"dpmpp-3m-sde",
"dpmpp-2m-sde",
"k-heun",
"k-lms",
"k-dpmpp-2s-ancestral",
"k-dpm-2",
"k-dpm-fast"
],
value="dpmpp-3m-sde"
)
steps_slider = gr.Slider(minimum=0, maximum=200, label="Steps", step=1)
steps_slider.value = 100 # Set the default value here
cfg_scale_slider = gr.Slider(minimum=0, maximum=15, label="CFG Scale", step=0.1)
cfg_scale_slider.value = 7 # Set the default value here
sigma_min_slider = gr.Slider(minimum=0, maximum=50, label="Sigma Min", step=0.1, value=0.3)
sigma_max_slider = gr.Slider(minimum=0, maximum=1000, label="Sigma Max", step=1, value=500)
generation_time_slider = gr.Slider(minimum=0, maximum=47, label="Generation Time (seconds)", step=1)
generation_time_slider.value = 47 # Set the default value here
seed_slider = gr.Slider(minimum=-1, maximum=999999, label="Seed", step=1)
seed_slider.value = 77212 # Set the default value here
output_textbox = gr.Textbox(label="Output")
title = "💀🔊 StableAudioWebUI 💀🔊"
description = "[Github Repository](https://github.com/Saganaki22/StableAudioWebUI)"
gr.Interface(
audio_generator,
[prompt_textbox, sampler_dropdown, steps_slider, cfg_scale_slider, sigma_min_slider, sigma_max_slider, generation_time_slider, seed_slider],
[gr.Audio(), output_textbox],
title=title,
description=description
).launch() |