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