Spaces:
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dropdown>radio, t-start percentage, intro text change
Browse files
app.py
CHANGED
@@ -20,7 +20,7 @@ LDM2_LARGE = "cvssp/audioldm2-large"
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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ldm2 = load_model(model_id=LDM2, device=device)
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ldm2_large = load_model(model_id=LDM2_LARGE, device=device)
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ldm2_music = load_model(model_id=
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def randomize_seed_fn(seed, randomize_seed):
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@@ -46,7 +46,6 @@ def invert(ldm_stable, x0, prompt_src, num_diffusion_steps, cfg_scale_src): # ,
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return zs, wts
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-
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def sample(ldm_stable, zs, wts, steps, prompt_tar, tstart, cfg_scale_tar): # , ldm_stable):
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# reverse process (via Zs and wT)
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tstart = torch.tensor(tstart, dtype=torch.int)
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@@ -71,14 +70,16 @@ def sample(ldm_stable, zs, wts, steps, prompt_tar, tstart, cfg_scale_tar): # ,
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return f.name
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def edit(input_audio,
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model_id: str,
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@@ -89,7 +90,7 @@ def edit(input_audio,
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steps=200,
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cfg_scale_src=3.5,
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cfg_scale_tar=12,
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t_start=
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randomize_seed=True):
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# global ldm_stable, current_loaded_model
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@@ -104,10 +105,8 @@ def edit(input_audio,
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ldm_stable = ldm2
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elif model_id == LDM2_LARGE:
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ldm_stable = ldm2_large
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else:
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ldm_stable = ldm2_music
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-
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# If the inversion was done for a different model, we need to re-run the inversion
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if not do_inversion and (saved_inv_model is None or saved_inv_model != model_id):
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@@ -123,25 +122,22 @@ def edit(input_audio,
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zs = gr.State(value=zs_tensor)
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saved_inv_model = model_id
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do_inversion = False
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-
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# make sure t_start is in the right limit
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t_start = change_tstart_range(t_start, steps)
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output = sample(ldm_stable, zs.value, wts.value, steps, prompt_tar=target_prompt,
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cfg_scale_tar=cfg_scale_tar)
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return output, wts, zs, saved_inv_model, do_inversion
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def get_example():
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case = [
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['Examples/Beethoven.wav',
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'',
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'A recording of an arcade game soundtrack.',
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'cvssp/audioldm2-music',
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'27s',
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'Examples/Beethoven_arcade.wav',
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@@ -149,7 +145,7 @@ def get_example():
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['Examples/Beethoven.wav',
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'A high quality recording of wind instruments and strings playing.',
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'A high quality recording of a piano playing.',
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'cvssp/audioldm2-music',
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'27s',
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'Examples/Beethoven_piano.wav',
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@@ -157,14 +153,14 @@ def get_example():
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['Examples/ModalJazz.wav',
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'Trumpets playing alongside a piano, bass and drums in an upbeat old-timey cool jazz song.',
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'A banjo playing alongside a piano, bass and drums in an upbeat old-timey cool country song.',
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-
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'cvssp/audioldm2-music',
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'106s',
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'Examples/ModalJazz_banjo.wav',],
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['Examples/Cat.wav',
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'',
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'A dog barking.',
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'cvssp/audioldm2-large',
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'10s',
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'Examples/Cat_dog.wav',]
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@@ -173,15 +169,15 @@ def get_example():
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intro = """
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<h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;">
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<h2 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> Audio
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<h3 style="margin-bottom: 10px; text-align: center;">
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<a href="https://arxiv.org/abs/2402.10009">[Paper]</a> |
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<a href="https://hilamanor.github.io/AudioEditing/">[Project page]</a> |
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<a href="https://github.com/HilaManor/AudioEditingCode">[Code]</a>
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</h3>
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<p style="font-size:large">
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Demo for the method introduced in:
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<b <a href="https://arxiv.org/abs/2402.10009" style="text-decoration: underline;" target="_blank"> Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion </a> </b>
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</p>
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<p style="font-size:larger">
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@@ -228,22 +224,24 @@ with gr.Blocks(css='style.css') as demo:
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output_audio = gr.Audio(label="Edited Audio", interactive=False, scale=1)
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with gr.Row():
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-
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-
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with gr.Row():
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with gr.Column():
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submit = gr.Button("Edit")
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with gr.Row():
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t_start = gr.Slider(minimum=10, maximum=240, value=30, step=1, label="T-start", interactive=True, scale=3,
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info="Higher T-start -> stronger edit. Lower T-start -> closer to original audio")
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model_id = gr.Dropdown(label="AudioLDM2 Version", choices=["cvssp/audioldm2",
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"cvssp/audioldm2-large",
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"cvssp/audioldm2-music"],
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info="Choose a checkpoint suitable for your intended audio and edit",
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value="cvssp/audioldm2-music", interactive=True, type="value", scale=2)
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with gr.Accordion("More Options", open=False):
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with gr.Row():
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src_prompt = gr.Textbox(label="Source Prompt", lines=2, interactive=True, info= "Optional: Describe the original audio input",
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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ldm2 = load_model(model_id=LDM2, device=device)
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ldm2_large = load_model(model_id=LDM2_LARGE, device=device)
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ldm2_music = load_model(model_id=MUSIC, device=device)
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def randomize_seed_fn(seed, randomize_seed):
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return zs, wts
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def sample(ldm_stable, zs, wts, steps, prompt_tar, tstart, cfg_scale_tar): # , ldm_stable):
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# reverse process (via Zs and wT)
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tstart = torch.tensor(tstart, dtype=torch.int)
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return f.name
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# def change_tstart_range(t_start, steps):
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# maximum = int(0.8 * steps)
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# minimum = int(0.15 * steps)
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# if t_start > maximum:
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# t_start = maximum
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# elif t_start < minimum:
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# t_start = minimum
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# return t_start
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def edit(input_audio,
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model_id: str,
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steps=200,
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cfg_scale_src=3.5,
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cfg_scale_tar=12,
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t_start=45,
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randomize_seed=True):
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# global ldm_stable, current_loaded_model
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ldm_stable = ldm2
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elif model_id == LDM2_LARGE:
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ldm_stable = ldm2_large
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else: # MUSIC
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ldm_stable = ldm2_music
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# If the inversion was done for a different model, we need to re-run the inversion
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if not do_inversion and (saved_inv_model is None or saved_inv_model != model_id):
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zs = gr.State(value=zs_tensor)
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saved_inv_model = model_id
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do_inversion = False
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# make sure t_start is in the right limit
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# t_start = change_tstart_range(t_start, steps)
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output = sample(ldm_stable, zs.value, wts.value, steps, prompt_tar=target_prompt,
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tstart=int(t_start / 100 * steps), cfg_scale_tar=cfg_scale_tar)
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return output, wts, zs, saved_inv_model, do_inversion
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def get_example():
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case = [
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['Examples/Beethoven.wav',
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'',
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'A recording of an arcade game soundtrack.',
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45,
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'cvssp/audioldm2-music',
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'27s',
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'Examples/Beethoven_arcade.wav',
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['Examples/Beethoven.wav',
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'A high quality recording of wind instruments and strings playing.',
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'A high quality recording of a piano playing.',
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45,
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'cvssp/audioldm2-music',
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'27s',
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'Examples/Beethoven_piano.wav',
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['Examples/ModalJazz.wav',
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'Trumpets playing alongside a piano, bass and drums in an upbeat old-timey cool jazz song.',
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'A banjo playing alongside a piano, bass and drums in an upbeat old-timey cool country song.',
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45,
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'cvssp/audioldm2-music',
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'106s',
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'Examples/ModalJazz_banjo.wav',],
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['Examples/Cat.wav',
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'',
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'A dog barking.',
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75,
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'cvssp/audioldm2-large',
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'10s',
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'Examples/Cat_dog.wav',]
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intro = """
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<h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> ZETA Editing 🎧 </h1>
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<h2 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> Zero-Shot Text-Based Audio Editing Using DDPM Inversion 🎛️ </h2>
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<h3 style="margin-bottom: 10px; text-align: center;">
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<a href="https://arxiv.org/abs/2402.10009">[Paper]</a> |
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<a href="https://hilamanor.github.io/AudioEditing/">[Project page]</a> |
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<a href="https://github.com/HilaManor/AudioEditingCode">[Code]</a>
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</h3>
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<p style="font-size:large">
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Demo for the text-based editing method introduced in:
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<b <a href="https://arxiv.org/abs/2402.10009" style="text-decoration: underline;" target="_blank"> Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion </a> </b>
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</p>
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<p style="font-size:larger">
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output_audio = gr.Audio(label="Edited Audio", interactive=False, scale=1)
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with gr.Row():
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tar_prompt = gr.Textbox(label="Prompt", info="Describe your desired edited output", placeholder="a recording of a happy upbeat arcade game soundtrack",
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lines=2, interactive=True)
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with gr.Row():
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t_start = gr.Slider(minimum=15, maximum=85, value=45, step=1, label="T-start (%)", interactive=True, scale=3,
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info="Higher T-start -> stronger edit. Lower T-start -> closer to original audio.")
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# model_id = gr.Dropdown(label="AudioLDM2 Version",
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model_id = gr.Radio(label="AudioLDM2 Version",
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choices=["cvssp/audioldm2",
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"cvssp/audioldm2-large",
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"cvssp/audioldm2-music"],
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info="Choose a checkpoint suitable for your intended audio and edit",
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value="cvssp/audioldm2-music", interactive=True, type="value", scale=2)
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with gr.Row():
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with gr.Column():
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submit = gr.Button("Edit")
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with gr.Accordion("More Options", open=False):
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with gr.Row():
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src_prompt = gr.Textbox(label="Source Prompt", lines=2, interactive=True, info= "Optional: Describe the original audio input",
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