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Browse files- .gitattributes +36 -0
- .gitignore +164 -0
- README.md +14 -0
- app.py +134 -0
- assets/bach.wav +3 -0
- requirements.txt +7 -0
.gitattributes
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.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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dist/
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downloads/
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eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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# Installer logs
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profile_default/
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# pyenv
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# intended to run in multiple environments; otherwise, check them in:
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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.pdm-python
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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celerybeat-schedule
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celerybeat.pid
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*.sage.py
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ENV/
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env.bak/
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venv.bak/
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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cython_debug/
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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.vscode/
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.ruff_cache/
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README.md
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---
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title: Audiobox Aesthetics
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emoji: 📚
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colorFrom: purple
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colorTo: red
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sdk: gradio
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sdk_version: 5.16.0
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app_file: app.py
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pinned: false
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license: cc-by-4.0
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short_description: Demo for audiobox-aesthetics
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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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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# This file is copied & modified from UNESCO/MMS/blob/main/asr.py
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import gradio as gr
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import numpy as np
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import torch
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import torchaudio
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import json
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from audiobox_aesthetics import infer as aes_infer
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import plotly.graph_objects as go
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ASR_EXAMPLES = [("assets/bach.wav")]
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aes_predictor = aes_infer.initialize_model(None)
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def transcribe(audio_data=None):
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if not audio_data:
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return "<<ERROR: Empty Audio Input>>"
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if isinstance(audio_data, tuple):
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# microphone
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sr, audio_samples = audio_data
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audio_samples = (audio_samples / 32768.0).astype(np.float32)
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audio_samples = torch.tensor(audio_samples)
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if audio_samples.ndim == 1:
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audio_samples = audio_samples[:, None]
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assert audio_samples.ndim == 2
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audio_samples = audio_samples.t()
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else:
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# file upload
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if not isinstance(audio_data, str):
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return "<<ERROR: Invalid Audio Input Instance: {}>>".format(
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type(audio_data)
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)
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audio_samples, sr = torchaudio.load(audio_data)
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transcription = json.loads(
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aes_predictor.forward([{"path": audio_samples, "sample_rate": sr}])[0]
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)
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# reorder like paper figures
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transcription = {
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"Production Quality": transcription["PQ"],
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"Production Complexity": transcription["PC"],
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"Content Enjoyment": transcription["CE"],
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"Content Usefulness": transcription["CU"],
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}
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# Create a Plotly bar plot
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fig = go.Figure()
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colors = ["#b1d8ff", "#fee2f5", "#cefac4", "#d2d3ff"]
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values = list(transcription.values())
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keys = list(transcription.keys())
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fig.add_trace(
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go.Bar(
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x=keys,
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y=values,
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text=[f"{v:.2f}" for v in values], # Format text to 2 decimal places
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textposition="outside", # Position text outside the bars
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marker=dict(color=colors),
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)
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)
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# Set the range for the y-axis
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fig.update_layout(
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yaxis=dict(range=[0, 10]),
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xaxis_title="Metrics",
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yaxis_title="Scores",
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)
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return fig
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main_interface = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(),
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],
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# outputs="text",
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outputs=gr.Plot(),
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examples=ASR_EXAMPLES,
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title="Audiobox Aesthetics Demo Prediction",
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description=("Play some audio through microphone or upload the file."),
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article="",
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allow_flagging="never",
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)
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disclaimer = """
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## Disclaimer
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"""
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99 |
+
with gr.Blocks() as demo:
|
100 |
+
gr.HTML(
|
101 |
+
"""
|
102 |
+
<div style="text-align: center;">
|
103 |
+
<h1>
|
104 |
+
Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound
|
105 |
+
</h1>
|
106 |
+
</div>
|
107 |
+
"""
|
108 |
+
)
|
109 |
+
|
110 |
+
gr.Markdown(
|
111 |
+
"<p align='center' style='font-size: 20px;'>See our <a href='https://arxiv.org/abs/2502.05139'>paper</a>, Github <a href='https://github.com/facebookresearch/audiobox-aesthetics'>repo</a> and HuggingFace <a href='https://huggingface.co/facebook/audiobox-aesthetics'>repo</a> </p>"
|
112 |
+
)
|
113 |
+
gr.HTML(
|
114 |
+
"""<center><a href="https://huggingface.co/spaces/facebook/audiobox-aesthetics?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 more control and no queue.</center>"""
|
115 |
+
)
|
116 |
+
|
117 |
+
main_interface.render()
|
118 |
+
|
119 |
+
gr.HTML(
|
120 |
+
"""
|
121 |
+
<div class="footer" style="text-align:center">
|
122 |
+
<p>
|
123 |
+
Model by <a href="https://ai.facebook.com" style="text-decoration: underline;" target="_blank">Meta AI</a> - Gradio Demo by 🤗 Hugging Face
|
124 |
+
</p>
|
125 |
+
</div>
|
126 |
+
"""
|
127 |
+
)
|
128 |
+
|
129 |
+
# with gr.Row():
|
130 |
+
# gr.Markdown(disclaimer)
|
131 |
+
|
132 |
+
if __name__ == "__main__":
|
133 |
+
demo.queue()
|
134 |
+
demo.launch()
|
assets/bach.wav
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e2bff9b5066c65e8b983d454f749559122a3039b42c513f8ed565cd9a6433402
|
3 |
+
size 1769550
|
requirements.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
pip>=23.2
|
2 |
+
gradio==5.16.0
|
3 |
+
torch>=2.2.0
|
4 |
+
torchaudio
|
5 |
+
tqdm
|
6 |
+
audiobox_aesthetics>=0.0.2
|
7 |
+
plotly==6.0.0
|