add app.py

.gitignore

@@ -0,0 +1,136 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Some extras
+wandb/
+logs/
+
+# ruff
+.ruff_cache/

app.py

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+import gradio as gr
+import torch
+import torchaudio
+from denoisers import WaveUNetModel
+
+MODEL = WaveUNetModel.from_pretrained("wrice/waveunet-vctk-24khz")
+
+def denoise(inputs):
+    sr, audio = inputs
+    audio = torch.from_numpy(audio)[None]
+    audio = audio / 32768.0
+
+    if sr != MODEL.config.sample_rate:
+        audio = torchaudio.functional.resample(audio, sr, MODEL.config.sample_rate)
+
+    chunk_size = MODEL.config.max_length
+
+    padding = abs(audio.size(-1) % chunk_size - chunk_size)
+    padded = torch.nn.functional.pad(audio, (0, padding))
+
+    clean = []
+    for i in range(0, padded.shape[-1], chunk_size):
+        audio_chunk = padded[:, i:i + chunk_size]
+        with torch.no_grad():
+            clean_chunk = MODEL(audio_chunk[None]).logits
+        clean.append(clean_chunk.squeeze(0))
+
+    denoised = torch.concat(clean)[:, :audio.shape[-1]].squeeze().clamp(-1.0, 1.0)
+    return MODEL.config.sample_rate, denoised.numpy()
+
+iface = gr.Interface(fn=denoise, inputs="audio", outputs="audio")
+iface.launch()

requirements.txt

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+pesq
+torch
+torchaudio
+pytorch-lightning
+pedalboard
+denoisers
+transformers
+librosa
+wandb