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import gradio as gr | ||
import numpy as np | ||
from audioldm import text_to_audio, build_model | ||
from plugin import AudioLDMPlugin | ||
from tuneflow_devkit import Runner | ||
from pathlib import Path | ||
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# from share_btn import community_icon_html, loading_icon_html, share_js | ||
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model_id = "haoheliu/AudioLDM-S-Full" | ||
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audioldm = build_model() | ||
# audioldm=None | ||
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# def predict(input, history=[]): | ||
# # tokenize the new input sentence | ||
# new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') | ||
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# # append the new user input tokens to the chat history | ||
# bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1) | ||
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# # generate a response | ||
# history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist() | ||
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# # convert the tokens to text, and then split the responses into lines | ||
# response = tokenizer.decode(history[0]).split("<|endoftext|>") | ||
# response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)] # convert to tuples of list | ||
# return response, history | ||
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def text2audio(text, duration, guidance_scale, random_seed, n_candidates): | ||
# print(text, length, guidance_scale) | ||
waveform = text_to_audio( | ||
audioldm, | ||
text, | ||
random_seed, | ||
duration=duration, | ||
guidance_scale=guidance_scale, | ||
n_candidate_gen_per_text=int(n_candidates), | ||
) # [bs, 1, samples] | ||
waveform = [ | ||
gr.make_waveform((16000, wave[0]), bg_image="bg.png") for wave in waveform | ||
] | ||
# waveform = [(16000, np.random.randn(16000)), (16000, np.random.randn(16000))] | ||
if len(waveform) == 1: | ||
waveform = waveform[0] | ||
return waveform | ||
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# iface = gr.Interface(fn=text2audio, inputs=[ | ||
# gr.Textbox(value="A man is speaking in a huge room", max_lines=1), | ||
# gr.Slider(2.5, 10, value=5, step=2.5), | ||
# gr.Slider(0, 5, value=2.5, step=0.5), | ||
# gr.Number(value=42) | ||
# ], outputs=[gr.Audio(label="Output", type="numpy"), gr.Audio(label="Output", type="numpy")], | ||
# allow_flagging="never" | ||
# ) | ||
# iface.launch(share=True) | ||
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css = """ | ||
a { | ||
color: inherit; | ||
text-decoration: underline; | ||
} | ||
.gradio-container { | ||
font-family: 'IBM Plex Sans', sans-serif; | ||
} | ||
.gr-button { | ||
color: white; | ||
border-color: #000000; | ||
background: #000000; | ||
} | ||
input[type='range'] { | ||
accent-color: #000000; | ||
} | ||
.dark input[type='range'] { | ||
accent-color: #dfdfdf; | ||
} | ||
.container { | ||
max-width: 730px; | ||
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) | ||
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with iface: | ||
gr.HTML( | ||
""" | ||
<div style="text-align: center; max-width: 700px; margin: 0 auto;"> | ||
<div | ||
style=" | ||
display: inline-flex; | ||
align-items: center; | ||
gap: 0.8rem; | ||
font-size: 1.75rem; | ||
" | ||
> | ||
<h1 style="font-weight: 900; margin-bottom: 7px; line-height: normal;"> | ||
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models | ||
</h1> | ||
</div> | ||
<p style="margin-bottom: 10px; font-size: 94%"> | ||
<a href="https://arxiv.org/abs/2301.12503">[Paper]</a> <a href="https://audioldm.github.io/">[Project page]</a> | ||
</p> | ||
</div> | ||
""" | ||
) | ||
with gr.Group(): | ||
with gr.Box(): | ||
############# Input | ||
textbox = gr.Textbox( | ||
value="A hammer is hitting a wooden surface", | ||
max_lines=1, | ||
label="Input your text here. Please ensure it is descriptive and of moderate length.", | ||
elem_id="prompt-in", | ||
) | ||
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with gr.Accordion("Click to modify detailed configurations", open=False): | ||
seed = gr.Number( | ||
value=42, | ||
label="Change this value (any integer number) will lead to a different generation result.", | ||
) | ||
duration = gr.Slider( | ||
2.5, 10, value=5, step=2.5, label="Duration (seconds)" | ||
) | ||
guidance_scale = gr.Slider( | ||
0, | ||
5, | ||
value=2.5, | ||
step=0.5, | ||
label="Guidance scale (Large => better quality and relavancy to text; Small => better diversity)", | ||
) | ||
n_candidates = gr.Slider( | ||
1, | ||
5, | ||
value=3, | ||
step=1, | ||
label="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", | ||
) | ||
############# Output | ||
# outputs=gr.Audio(label="Output", type="numpy") | ||
outputs = gr.Video(label="Output", elem_id="output-video") | ||
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# with gr.Group(elem_id="container-advanced-btns"): | ||
# # advanced_button = gr.Button("Advanced options", elem_id="advanced-btn") | ||
# with gr.Group(elem_id="share-btn-container"): | ||
# community_icon = gr.HTML(community_icon_html, visible=False) | ||
# loading_icon = gr.HTML(loading_icon_html, visible=False) | ||
# share_button = gr.Button("Share to community", elem_id="share-btn", visible=False) | ||
# outputs=[gr.Audio(label="Output", type="numpy"), gr.Audio(label="Output", type="numpy")] | ||
btn = gr.Button("Submit").style(full_width=True) | ||
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# 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") | ||
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btn.click( | ||
text2audio, | ||
inputs=[textbox, duration, guidance_scale, seed, n_candidates], | ||
outputs=[outputs], | ||
) | ||
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# share_button.click(None, [], [], _js=share_js) | ||
gr.HTML( | ||
""" | ||
<div class="footer" style="text-align: center; max-width: 700px; margin: 0 auto;"> | ||
<p>Follow the latest update of AudioLDM on our<a href="https://github.com/haoheliu/AudioLDM" style="text-decoration: underline;" target="_blank"> Github repo</a> | ||
</p> | ||
<br> | ||
<p>Model by <a href="https://twitter.com/LiuHaohe" style="text-decoration: underline;" target="_blank">Haohe Liu</a></p> | ||
<br> | ||
</div> | ||
""" | ||
) | ||
gr.Examples( | ||
[ | ||
["A hammer is hitting a wooden surface", 5, 2.5, 45, 3], | ||
[ | ||
"Peaceful and calming ambient music with singing bowl and other instruments.", | ||
5, | ||
2.5, | ||
45, | ||
3, | ||
], | ||
["A man is speaking in a small room.", 5, 2.5, 45, 3], | ||
["A female is speaking followed by footstep sound", 5, 2.5, 45, 3], | ||
[ | ||
"Wooden table tapping sound followed by water pouring sound.", | ||
5, | ||
2.5, | ||
45, | ||
3, | ||
], | ||
], | ||
fn=text2audio, | ||
inputs=[textbox, duration, guidance_scale, seed, n_candidates], | ||
outputs=[outputs], | ||
cache_examples=True, | ||
) | ||
with gr.Accordion("Additional information", open=False): | ||
gr.HTML( | ||
""" | ||
<div class="acknowledgments"> | ||
<p> We build the model with data from <a href="http://research.google.com/audioset/">AudioSet</a>, <a href="https://freesound.org/">Freesound</a> and <a href="https://sound-effects.bbcrewind.co.uk/">BBC Sound Effect library</a>. We share this demo based on the <a href="https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/375954/Research.pdf">UK copyright exception</a> of data for academic research. </p> | ||
</div> | ||
""" | ||
) | ||
# <p>This demo is strictly for research demo purpose only. For commercial use please <a href="haoheliu@gmail.com">contact us</a>.</p> | ||
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iface.queue(concurrency_count=3) | ||
# iface.launch(debug=True) | ||
iface.launch(debug=True, share=True) | ||
app = Runner(plugin_class_list=[AudioLDMPlugin], bundle_file_path=str( | ||
Path(__file__).parent.joinpath('bundle.json').absolute())).start(path_prefix='/plugins/audio-ldm') |
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