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Running
on
A10G
| import gradio as gr | |
| import numpy as np | |
| from audioldm import text_to_audio, build_model | |
| from share_btn import community_icon_html, loading_icon_html, share_js | |
| model_id="haoheliu/AudioLDM-S-Full" | |
| audioldm = build_model() | |
| # audioldm=None | |
| # def predict(input, history=[]): | |
| # # tokenize the new input sentence | |
| # new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') | |
| # # append the new user input tokens to the chat history | |
| # bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1) | |
| # # generate a response | |
| # history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist() | |
| # # 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 | |
| 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 | |
| # 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) | |
| 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) | |
| 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> | |
| """ | |
| ) | |
| gr.HTML(""" | |
| <h1 style="font-weight: 900; margin-bottom: 7px;"> | |
| AudioLDM: Text-to-Audio Generation with Latent Diffusion Models | |
| </h1> | |
| <p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. | |
| <br/> | |
| <a href="https://huggingface.co/spaces/haoheliu/audioldm-text-to-audio-generation?duplicate=true"> | |
| <img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> | |
| <p/> | |
| """) | |
| 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") | |
| 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") | |
| # 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) | |
| 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, duration, guidance_scale, seed, n_candidates], outputs=[outputs]) | |
| 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> | |
| iface.queue(concurrency_count=3) | |
| iface.launch(debug=True) | |
| # iface.launch(debug=True, share=True) | |