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app.py
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import gradio as gr
import random
import torch
from torch import inference_mode
# from tempfile import NamedTemporaryFile
from typing import Optional
import numpy as np
from models import load_model
import utils
import spaces
from inversion_utils import inversion_forward_process, inversion_reverse_process
# ===
intro = """
<h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> MusicMagus </h1>
<h2 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> Zero-Shot Text-to-Music Editing via Diffusion Models </h2>
<h3 style="margin-bottom: 10px; text-align: center;">
<a href="https://arxiv.org/abs/2402.06178">[Paper]</a> |
<a href="https://wry-neighbor-173.notion.site/MusicMagus-Zero-Shot-Text-to-Music-Editing-via-Diffusion-Models-8f55a82f34944eb9a4028ca56c546d9d">[Demo page]</a> |
<a href="https://github.com/ldzhangyx/MusicMagus">[Code]</a>
</h3>
"""
help = """
<div style="font-size:medium">
<b>Instructions:</b><br>
<ul style="line-height: normal">
<li>You must provide an input audio and a target prompt to edit the audio. </li>
<li>T<sub>start</sub> is used to control the tradeoff between fidelity to the original signal and text-adhearance.
Lower value -> favor fidelity. Higher value -> apply a stronger edit.</li>
<li>Make sure that you use an AudioLDM2 version that is suitable for your input audio.
For example, use the music version for music and the large version for general audio.
</li>x
<li>You can additionally provide a source prompt to guide even further the editing process.</li>
<li>Longer input will take more time.</li>
<li><strong>Unlimited length</strong>: This space automatically trims input audio to a maximum length of 30 seconds.
For unlimited length, duplicated the space, and remove the trimming by changing the code.
Specifically, in the <code style="display:inline; background-color: lightgrey; ">load_audio</code> function in the <code style="display:inline; background-color: lightgrey; ">utils.py</code> file,
change <code style="display:inline; background-color: lightgrey; ">duration = min(audioldm.utils.get_duration(audio_path), 30)</code> to
<code style="display:inline; background-color: lightgrey; ">duration = audioldm.utils.get_duration(audio_path)</code>.
</ul>
</div>
"""
with gr.Blocks(css='style.css') as demo: #, delete_cache=(3600, 3600)) as demo:
def reset_do_inversion(do_inversion_user, do_inversion):
# do_inversion = gr.State(value=True)
do_inversion = True
do_inversion_user = True
return do_inversion_user, do_inversion
# handle the case where the user clicked the button but the inversion was not done
def clear_do_inversion_user(do_inversion_user):
do_inversion_user = False
return do_inversion_user
def post_match_do_inversion(do_inversion_user, do_inversion):
if do_inversion_user:
do_inversion = True
do_inversion_user = False
return do_inversion_user, do_inversion
gr.HTML(intro)
wts = gr.State()
zs = gr.State()
wtszs = gr.State()
# cache_dir = gr.State(demo.GRADIO_CACHE)
saved_inv_model = gr.State()
# current_loaded_model = gr.State(value="cvssp/audioldm2-music")
# ldm_stable = load_model("cvssp/audioldm2-music", device, 200)
# ldm_stable = gr.State(value=ldm_stable)
do_inversion = gr.State(value=True) # To save some runtime when editing the same thing over and over
do_inversion_user = gr.State(value=False)
with gr.Group():
gr.Markdown("💡 **note**: input longer than **30 sec** is automatically trimmed (for unlimited input, see the Help section below)")
with gr.Row():
input_audio = gr.Audio(sources=["upload", "microphone"], type="filepath", editable=True, label="Input Audio",
interactive=True, scale=1)
output_audio = gr.Audio(label="Edited Audio", interactive=False, scale=1)
with gr.Row():
tar_prompt = gr.Textbox(label="Prompt", info="Describe your desired edited output",
placeholder="a recording of a happy upbeat arcade game soundtrack",
lines=2, interactive=True)
with gr.Row():
t_start = gr.Slider(minimum=15, maximum=85, value=45, step=1, label="T-start (%)", interactive=True, scale=3,
info="Lower T-start -> closer to original audio. Higher T-start -> stronger edit.")
# model_id = gr.Radio(label="AudioLDM2 Version",
model_id = gr.Dropdown(label="AudioLDM2 Version",
choices=["cvssp/audioldm2",
"cvssp/audioldm2-large",
"cvssp/audioldm2-music"],
info="Choose a checkpoint suitable for your intended audio and edit",
value="cvssp/audioldm2-music", interactive=True, type="value", scale=2)
with gr.Row():
with gr.Column():
submit = gr.Button("Edit")
with gr.Accordion("More Options", open=False):
with gr.Row():
src_prompt = gr.Textbox(label="Source Prompt", lines=2, interactive=True,
info="Optional: Describe the original audio input",
placeholder="A recording of a happy upbeat classical music piece",)
with gr.Row():
cfg_scale_src = gr.Number(value=3, minimum=0.5, maximum=25, precision=None,
label="Source Guidance Scale", interactive=True, scale=1)
cfg_scale_tar = gr.Number(value=12, minimum=0.5, maximum=25, precision=None,
label="Target Guidance Scale", interactive=True, scale=1)
steps = gr.Number(value=50, step=1, minimum=20, maximum=300,
info="Higher values (e.g. 200) yield higher-quality generation.",
label="Num Diffusion Steps", interactive=True, scale=1)
with gr.Row():
seed = gr.Number(value=0, precision=0, label="Seed", interactive=True)
randomize_seed = gr.Checkbox(label='Randomize seed', value=False)
length = gr.Number(label="Length", interactive=False, visible=False)
with gr.Accordion("Help💡", open=False):
gr.HTML(help)
submit.click(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=[seed], queue=False).then(
fn=clear_do_inversion_user, inputs=[do_inversion_user], outputs=[do_inversion_user]).then(
fn=edit,
inputs=[#cache_dir,
input_audio,
model_id,
do_inversion,
# current_loaded_model, ldm_stable,
wts, zs,
# wtszs,
saved_inv_model,
src_prompt,
tar_prompt,
steps,
cfg_scale_src,
cfg_scale_tar,
t_start,
randomize_seed
],
outputs=[output_audio, wts, zs, # wtszs,
saved_inv_model, do_inversion] # , current_loaded_model, ldm_stable],
).then(post_match_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion]
).then(lambda x: (demo.temp_file_sets.append(set([str(gr.utils.abspath(x))])) if type(x) is str else None),
inputs=wtszs)
# demo.move_resource_to_block_cache(wtszs.value)
# If sources changed we have to rerun inversion
input_audio.change(fn=reset_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion])
src_prompt.change(fn=reset_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion])
model_id.change(fn=reset_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion])
cfg_scale_src.change(fn=reset_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion])
steps.change(fn=reset_do_inversion, inputs=[do_inversion_user, do_inversion], outputs=[do_inversion_user, do_inversion])
gr.Examples(
label="Examples",
examples=get_example(),
inputs=[input_audio, src_prompt, tar_prompt, t_start, model_id, length, output_audio],
outputs=[output_audio]
)
demo.queue()
demo.launch(state_session_capacity=15)