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""" |
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Copyright (c) Meta Platforms, Inc. and affiliates. |
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All rights reserved. |
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This source code is licensed under the license found in the |
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LICENSE file in the root directory of this source tree. |
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""" |
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from tempfile import NamedTemporaryFile |
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import torch |
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import gradio as gr |
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from audiocraft.models import MusicGen |
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from audiocraft.data.audio import audio_write |
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MODEL = None |
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img_to_text = gr.load(name="spaces/fffiloni/CLIP-Interrogator-2") |
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def load_model(version): |
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print("Loading model", version) |
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return MusicGen.get_pretrained(version) |
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def predict(uploaded_image, melody, duration): |
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text = img_to_text(uploaded_image, 'best', 4, fn_index=1)[0] |
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global MODEL |
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topk = int(250) |
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if MODEL is None or MODEL.name != "melody": |
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MODEL = load_model("melody") |
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if duration > MODEL.lm.cfg.dataset.segment_duration: |
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raise gr.Error("MusicGen currently supports durations of up to 30 seconds!") |
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MODEL.set_generation_params( |
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use_sampling=True, |
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top_k=250, |
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top_p=0, |
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temperature=1.0, |
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cfg_coef=3.0, |
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duration=duration, |
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) |
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if melody: |
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sr, melody = melody[0], torch.from_numpy(melody[1]).to(MODEL.device).float().t().unsqueeze(0) |
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print(melody.shape) |
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if melody.dim() == 2: |
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melody = melody[None] |
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melody = melody[..., :int(sr * MODEL.lm.cfg.dataset.segment_duration)] |
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output = MODEL.generate_with_chroma( |
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descriptions=[text], |
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melody_wavs=melody, |
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melody_sample_rate=sr, |
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progress=False |
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) |
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else: |
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output = MODEL.generate(descriptions=[text], progress=False) |
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output = output.detach().cpu().float()[0] |
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with NamedTemporaryFile("wb", suffix=".wav", delete=False) as file: |
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audio_write(file.name, output, MODEL.sample_rate, strategy="loudness", add_suffix=False) |
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return file.name |
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with gr.Blocks() as demo: |
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gr.Markdown( |
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""" |
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# Image to MusicGen |
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This is the demo by @fffiloni for Image to [MusicGen](https://github.com/facebookresearch/audiocraft), a simple and controllable model for music generation |
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presented at: ["Simple and Controllable Music Generation"](https://huggingface.co/papers/2306.05284), using Clip Interrogator to get an image description as init text. |
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<br/> |
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<a href="https://huggingface.co/spaces/musicgen/MusicGen?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank"> |
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<img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> |
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for longer sequences, more control and no queue.</p> |
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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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with gr.Column(): |
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uploaded_image = gr.Image(label="Input Image", interactive=True, source="upload", type="filepath") |
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melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=True) |
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with gr.Row(): |
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submit = gr.Button("Submit") |
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with gr.Row(): |
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duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Duration", interactive=True) |
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with gr.Column(): |
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output = gr.Audio(label="Generated Music") |
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submit.click(predict, inputs=[uploaded_image, melody, duration], outputs=[output]) |
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gr.Markdown( |
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""" |
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### More details |
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The model will generate a short music extract based on the image you provided. |
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You can generate up to 30 seconds of audio. |
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This demo is set to use only the Melody model |
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1. Melody -- a music generation model capable of generating music condition on text and melody inputs. **Note**, you can also use text only. |
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2. Small -- a 300M transformer decoder conditioned on text only. |
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3. Medium -- a 1.5B transformer decoder conditioned on text only. |
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4. Large -- a 3.3B transformer decoder conditioned on text only (might OOM for the longest sequences.) |
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When using `melody`, ou can optionaly provide a reference audio from |
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which a broad melody will be extracted. The model will then try to follow both the description and melody provided. |
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You can also use your own GPU or a Google Colab by following the instructions on our repo. |
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See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft) |
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for more details. |
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""" |
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) |
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demo.queue(max_size=32).launch() |
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