import gradio as gr
import torch
from diffusers import AudioLDM2Pipeline
from share_btn import community_icon_html, loading_icon_html, share_js
# make Space compatible with CPU duplicates
if torch.cuda.is_available():
device = "cuda"
torch_dtype = torch.float16
else:
device = "cpu"
torch_dtype = torch.float32
# load the diffusers pipeline
repo_id = "cvssp/audioldm2"
pipe = AudioLDM2Pipeline.from_pretrained(repo_id, torch_dtype=torch_dtype).to(device)
# pipe.unet = torch.compile(pipe.unet)
# set the generator for reproducibility
generator = torch.Generator(device)
def text2audio(text, negative_prompt, duration, guidance_scale, random_seed, n_candidates):
if text is None:
raise gr.Error("Please provide a text input.")
waveforms = pipe(
text,
audio_length_in_s=duration,
guidance_scale=guidance_scale,
num_inference_steps=200,
negative_prompt=negative_prompt,
num_waveforms_per_prompt=n_candidates if n_candidates else 1,
generator=generator.manual_seed(int(random_seed)),
)["audios"]
return gr.make_waveform((16000, waveforms[0]), bg_image="bg.png")
css = """
a {
color: inherit;
text-decoration: underline;
}
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
max-width: 730px !important;
}
.gr-button {
color: white;
border-color: #000000;
background: #000000;
}
input[type='range'] {
accent-color: #000000;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
margin: auto;
padding-top: 1.5rem;
}
#gallery {
min-height: 22rem;
margin-bottom: 15px;
margin-left: auto;
margin-right: auto;
border-bottom-right-radius: .5rem !important;
border-bottom-left-radius: .5rem !important;
}
#gallery>div>.h-full {
min-height: 20rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
#advanced-btn {
font-size: .7rem !important;
line-height: 19px;
margin-top: 12px;
margin-bottom: 12px;
padding: 2px 8px;
border-radius: 14px !important;
}
#advanced-options {
margin-bottom: 20px;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.acknowledgments h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
#container-advanced-btns{
display: flex;
flex-wrap: wrap;
justify-content: space-between;
align-items: center;
}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
#share-btn-container {
display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
margin-top: 10px;
margin-left: auto;
}
#share-btn {
all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0;
}
#share-btn * {
all: unset;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
.gr-form{
flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
}
#prompt-container{
gap: 0;
}
#generated_id{
min-height: 700px
}
#setting_id{
margin-bottom: 12px;
text-align: center;
font-weight: 900;
}
"""
iface = gr.Blocks(css=css)
with iface:
gr.HTML(
"""
"""
)
gr.HTML(
"""
This is the demo for AudioLDM 2, powered by 🧨 Diffusers. Demo uses the checkpoint AudioLDM 2 base. For faster inference without waiting in
queue, you may duplicate the space and upgrade to a GPU in the settings.
"""
)
with gr.Group():
with gr.Box():
textbox = gr.Textbox(
value="The vibrant beat of Brazilian samba drums.",
max_lines=1,
label="Input text",
info="Your text is important for the audio quality. Please ensure it is descriptive by using more adjectives.",
elem_id="prompt-in",
)
negative_textbox = gr.Textbox(
value="Low quality.",
max_lines=1,
label="Negative prompt",
info="Enter a negative prompt not to guide the audio generation. Selecting appropriate negative prompts can improve the audio quality significantly.",
elem_id="prompt-in",
)
with gr.Accordion("Click to modify detailed configurations", open=False):
seed = gr.Number(
value=45,
label="Seed",
info="Change this value (any integer number) will lead to a different generation result.",
)
duration = gr.Slider(5, 15, value=10, step=2.5, label="Duration (seconds)")
guidance_scale = gr.Slider(
0,
7,
value=3.5,
step=0.5,
label="Guidance scale",
info="Larger => better quality and relevancy to text; Smaller => better diversity",
)
n_candidates = gr.Slider(
1,
5,
value=3,
step=1,
label="Number waveforms to generate",
info="Automatic quality control. This number control the number of candidates (e.g., generate three audios and choose the best to show you). A larger value usually lead to better quality with heavier computation",
)
outputs = gr.Video(label="Output", elem_id="output-video")
btn = gr.Button("Submit").style(full_width=True)
with gr.Group(elem_id="share-btn-container", visible=False):
community_icon = gr.HTML(community_icon_html)
loading_icon = gr.HTML(loading_icon_html)
share_button = gr.Button("Share to community", elem_id="share-btn")
btn.click(
text2audio,
inputs=[textbox, negative_textbox, duration, guidance_scale, seed, n_candidates],
outputs=[outputs],
)
share_button.click(None, [], [], _js=share_js)
gr.HTML(
"""
"""
)
gr.Examples(
[
["A hammer is hitting a wooden surface.", "Low quality.", 10, 3.5, 45, 3],
["A cat is meowing for attention.", "Low quality.", 10, 3.5, 45, 3],
["An excited crowd cheering at a sports game.", "Low quality.", 10, 3.5, 45, 3],
["Birds singing sweetly in a blooming garden.", "Low quality.", 10, 3.5, 45, 3],
["A modern synthesizer creating futuristic soundscapes.", "Low quality.", 10, 3.5, 45, 3],
["The vibrant beat of Brazilian samba drums.", "Low quality.", 10, 3.5, 45, 3],
],
fn=text2audio,
inputs=[textbox, negative_textbox, duration, guidance_scale, seed, n_candidates],
outputs=[outputs],
cache_examples=True,
)
gr.HTML(
"""
Essential Tricks for Enhancing the Quality of Your Generated
Audio
1. Try using more adjectives to describe your sound. For example: "A man is speaking
clearly and slowly in a large room" is better than "A man is speaking".
2. Try using different random seeds, which can significantly affect the quality of the generated
output.
3. It's better to use general terms like 'man' or 'woman' instead of specific names for individuals or
abstract objects that humans may not be familiar with.
4. Using a negative prompt to not guide the diffusion process can improve the
audio quality significantly. Try using negative prompts like 'low quality'.
"""
)
with gr.Accordion("Additional information", open=False):
gr.HTML(
"""
"""
)
iface.queue(max_size=20).launch()