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import gradio as gr |
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import torch |
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from diffusers import AudioLDMPipeline |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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from transformers import AutoProcessor, ClapModel |
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if torch.cuda.is_available(): |
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device = "cuda" |
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torch_dtype = torch.float16 |
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else: |
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device = "cpu" |
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torch_dtype = torch.float32 |
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repo_id = "cvssp/audioldm-m-full" |
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pipe = AudioLDMPipeline.from_pretrained(repo_id, torch_dtype=torch_dtype).to(device) |
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pipe.unet = torch.compile(pipe.unet) |
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clap_model = ClapModel.from_pretrained("sanchit-gandhi/clap-htsat-unfused-m-full").to(device) |
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processor = AutoProcessor.from_pretrained("sanchit-gandhi/clap-htsat-unfused-m-full") |
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generator = torch.Generator(device) |
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def text2audio(text, negative_prompt, duration, guidance_scale, random_seed, n_candidates): |
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if text is None: |
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raise gr.Error("Please provide a text input.") |
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waveforms = pipe( |
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text, |
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audio_length_in_s=duration, |
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guidance_scale=guidance_scale, |
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negative_prompt=negative_prompt, |
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num_waveforms_per_prompt=n_candidates if n_candidates else 1, |
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generator=generator.manual_seed(int(random_seed)), |
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)["audios"] |
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if waveforms.shape[0] > 1: |
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waveform = score_waveforms(text, waveforms) |
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else: |
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waveform = waveforms[0] |
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return gr.make_waveform((16000, waveform), bg_image="bg.png") |
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def score_waveforms(text, waveforms): |
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inputs = processor(text=text, audios=list(waveforms), return_tensors="pt", padding=True) |
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inputs = {key: inputs[key].to(device) for key in inputs} |
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with torch.no_grad(): |
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logits_per_text = clap_model(**inputs).logits_per_text |
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probs = logits_per_text.softmax(dim=-1) |
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most_probable = torch.argmax(probs) |
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waveform = waveforms[most_probable] |
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return waveform |
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css = """ |
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a { |
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color: inherit; text-decoration: underline; |
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} .gradio-container { |
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font-family: 'IBM Plex Sans', sans-serif; |
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} .gr-button { |
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color: white; border-color: #000000; background: #000000; |
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} input[type='range'] { |
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accent-color: #000000; |
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} .dark input[type='range'] { |
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accent-color: #dfdfdf; |
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} .container { |
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max-width: 730px; margin: auto; padding-top: 1.5rem; |
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} #gallery { |
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min-height: 22rem; margin-bottom: 15px; margin-left: auto; margin-right: auto; border-bottom-right-radius: |
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.5rem !important; border-bottom-left-radius: .5rem !important; |
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} #gallery>div>.h-full { |
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min-height: 20rem; |
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} .details:hover { |
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text-decoration: underline; |
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} .gr-button { |
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white-space: nowrap; |
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} .gr-button:focus { |
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border-color: rgb(147 197 253 / var(--tw-border-opacity)); outline: none; box-shadow: |
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var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); --tw-border-opacity: 1; |
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--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) |
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var(--tw-ring-offset-color); --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px |
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var(--tw-ring-offset-width)) var(--tw-ring-color); --tw-ring-color: rgb(191 219 254 / |
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var(--tw-ring-opacity)); --tw-ring-opacity: .5; |
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} #advanced-btn { |
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font-size: .7rem !important; line-height: 19px; margin-top: 12px; margin-bottom: 12px; padding: 2px 8px; |
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border-radius: 14px !important; |
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} #advanced-options { |
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margin-bottom: 20px; |
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} .footer { |
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margin-bottom: 45px; margin-top: 35px; text-align: center; border-bottom: 1px solid #e5e5e5; |
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} .footer>p { |
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font-size: .8rem; display: inline-block; padding: 0 10px; transform: translateY(10px); background: white; |
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} .dark .footer { |
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border-color: #303030; |
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} .dark .footer>p { |
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background: #0b0f19; |
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} .acknowledgments h4{ |
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margin: 1.25em 0 .25em 0; font-weight: bold; font-size: 115%; |
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} #container-advanced-btns{ |
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display: flex; flex-wrap: wrap; justify-content: space-between; align-items: center; |
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} .animate-spin { |
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animation: spin 1s linear infinite; |
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} @keyframes spin { |
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from { |
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transform: rotate(0deg); |
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} to { |
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transform: rotate(360deg); |
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} |
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} #share-btn-container { |
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display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: |
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#000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; |
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margin-top: 10px; margin-left: auto; |
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} #share-btn { |
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all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; |
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margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem |
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!important;right:0; |
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} #share-btn * { |
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all: unset; |
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} #share-btn-container div:nth-child(-n+2){ |
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width: auto !important; min-height: 0px !important; |
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} #share-btn-container .wrap { |
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display: none !important; |
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} .gr-form{ |
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flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0; |
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} #prompt-container{ |
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gap: 0; |
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} #generated_id{ |
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min-height: 700px |
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} #setting_id{ |
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margin-bottom: 12px; text-align: center; font-weight: 900; |
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} |
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""" |
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iface = gr.Blocks(css=css) |
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with iface: |
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gr.HTML( |
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""" |
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<div style="text-align: center; max-width: 700px; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; align-items: center; gap: 0.8rem; font-size: 1.75rem; |
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" |
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> |
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<h1 style="font-weight: 900; margin-bottom: 7px; line-height: normal;"> |
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AudioLDM: Text-to-Audio Generation with Latent Diffusion Models |
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</h1> |
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</div> <p style="margin-bottom: 10px; font-size: 94%"> |
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<a href="https://arxiv.org/abs/2301.12503">[Paper]</a> <a href="https://audioldm.github.io/">[Project |
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page]</a> <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/audioldm">[🧨 |
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Diffusers]</a> |
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</p> |
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</div> |
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""" |
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) |
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gr.HTML( |
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""" |
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<p>This is the demo for AudioLDM, powered by 🧨 Diffusers. Demo uses the checkpoint <a |
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href="https://huggingface.co/cvssp/audioldm-m-full"> audioldm-m-full </a>. For faster inference without waiting in |
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queue, you may duplicate the space and upgrade to a GPU in the settings. <br/> <a |
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href="https://huggingface.co/spaces/haoheliu/audioldm-text-to-audio-generation?duplicate=true"> <img |
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style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> <p/> |
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""" |
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) |
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with gr.Group(): |
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with gr.Box(): |
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textbox = gr.Textbox( |
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value="", |
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max_lines=1, |
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label="Input text", |
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info="Your text is important for the audio quality. Please ensure it is descriptive by using more adjectives.", |
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elem_id="prompt-in", |
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) |
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negative_textbox = gr.Textbox( |
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value="low quality, average quality", |
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max_lines=1, |
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label="Negative prompt", |
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info="Enter a negative prompt not to guide the audio generation. Selecting appropriate negative prompts can improve the audio quality significantly.", |
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elem_id="prompt-in", |
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) |
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with gr.Accordion("Click to modify detailed configurations", open=False): |
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seed = gr.Number( |
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value=45, |
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label="Seed", |
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info="Change this value (any integer number) will lead to a different generation result.", |
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) |
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duration = gr.Slider(2.5, 10, value=5, step=2.5, label="Duration (seconds)") |
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guidance_scale = gr.Slider( |
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0, |
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4, |
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value=2.5, |
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step=0.5, |
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label="Guidance scale", |
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info="Large => better quality and relevancy to text; Small => better diversity", |
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) |
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n_candidates = gr.Slider( |
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1, |
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3, |
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value=3, |
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step=1, |
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label="Number waveforms to generate", |
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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", |
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) |
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outputs = gr.Video(label="Output", elem_id="output-video") |
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btn = gr.Button("Submit").style(full_width=True) |
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with gr.Group(elem_id="share-btn-container", visible=False): |
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community_icon = gr.HTML(community_icon_html) |
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loading_icon = gr.HTML(loading_icon_html) |
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share_button = gr.Button("Share to community", elem_id="share-btn") |
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btn.click( |
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text2audio, |
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inputs=[textbox, negative_textbox, duration, guidance_scale, seed, n_candidates], |
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outputs=[outputs], |
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api_name="generate" |
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) |
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share_button.click(None, [], [], _js=share_js) |
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gr.HTML( |
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""" |
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<div class="footer" style="text-align: center; max-width: 700px; margin: 0 auto;"> |
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<p>Follow the latest update of AudioLDM on our<a href="https://github.com/haoheliu/AudioLDM" |
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style="text-decoration: underline;" target="_blank"> Github repo</a> </p> <br> <p>Model by <a |
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href="https://twitter.com/LiuHaohe" style="text-decoration: underline;" target="_blank">Haohe |
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Liu</a>. Code and demo by 🤗 Hugging Face.</p> <br> |
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</div> |
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""" |
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) |
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gr.Examples( |
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[ |
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["A hammer is hitting a wooden surface", "low quality, average quality", 5, 2.5, 45, 3], |
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["Peaceful and calming ambient music with singing bowl and other instruments.", "low quality, average quality", 5, 2.5, 45, 3], |
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["A man is speaking in a small room.", "low quality, average quality", 5, 2.5, 45, 3], |
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["A female is speaking followed by footstep sound", "low quality, average quality", 5, 2.5, 45, 3], |
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["Wooden table tapping sound followed by water pouring sound.", "low quality, average quality", 5, 2.5, 45, 3], |
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], |
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fn=text2audio, |
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inputs=[textbox, negative_textbox, duration, guidance_scale, seed, n_candidates], |
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outputs=[outputs], |
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cache_examples=True, |
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) |
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gr.HTML( |
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""" |
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<div class="acknowledgements"> <p>Essential Tricks for Enhancing the Quality of Your Generated |
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Audio</p> <p>1. Try to use more adjectives to describe your sound. For example: "A man is speaking |
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clearly and slowly in a large room" is better than "A man is speaking". This can make sure AudioLDM |
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understands what you want.</p> <p>2. Try to use different random seeds, which can affect the generation |
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quality significantly sometimes.</p> <p>3. It's better to use general terms like 'man' or 'woman' |
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instead of specific names for individuals or abstract objects that humans may not be familiar with, |
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such as 'mummy'.</p> <p>4. Using a negative prompt to not guide the diffusion process can improve the |
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audio quality significantly. Try using negative prompts like 'low quality'.</p> </div> |
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""" |
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) |
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with gr.Accordion("Additional information", open=False): |
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gr.HTML( |
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""" |
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<div class="acknowledgments"> |
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<p> We build the model with data from <a href="http://research.google.com/audioset/">AudioSet</a>, |
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<a href="https://freesound.org/">Freesound</a> and <a |
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href="https://sound-effects.bbcrewind.co.uk/">BBC Sound Effect library</a>. We share this demo |
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based on the <a |
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href="https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/375954/Research.pdf">UK |
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copyright exception</a> of data for academic research. </p> |
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</div> |
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""" |
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) |
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iface.queue(max_size=10).launch(debug=True) |
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