Initial commit from private spleeter

.gitignore

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+# 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/
+*.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/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# 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/
+.vscode
+.DS_Store
+__pycache__
+**/reporting
+
+pretrained_models
+docs/build
+.vscode

LICENSE

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+MIT License
+
+Copyright (c) 2019-present, Deezer SA.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

MANIFEST.in

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+include src/resources/*.json
+include README.md
+include LICENSE

Makefile

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+# =======================================================
+# Build script for distribution packaging.
+#
+# @author Deezer Research <[email protected]>
+# @licence MIT Licence
+# =======================================================
+
+clean:
+	rm -Rf *.egg-info
+	rm -Rf dist
+
+build:
+	@echo "=== Build CPU bdist package" 
+	@python3 setup.py sdist
+	@echo "=== CPU version checksum"
+	@openssl sha256 dist/*.tar.gz
+
+build-gpu:
+	@echo "=== Build GPU bdist package" 
+	@python3 setup.py sdist --target gpu
+	@echo "=== GPU version checksum"
+	@openssl sha256 dist/*.tar.gz
+
+upload:
+	twine upload dist/*
+
+test-upload:
+	twine upload --repository-url https://test.pypi.org/legacy/ dist/*
+
+all: clean build build-gpu upload

README.md

@@ -1,6 +1,64 @@
-# spleeter
+<img src="https://github.com/deezer/spleeter/raw/master/images/spleeter_logo.png" height="80" />
 
-<img src=images/spleeter_logo.png height=100>
+[![PyPI version](https://badge.fury.io/py/spleeter.svg)](https://badge.fury.io/py/spleeter) ![Conda](https://img.shields.io/conda/dn/conda-forge/spleeter)
 
+## About
 
-spleeter will be made available soon!
+**Spleeter** is the [Deezer](https://www.deezer.com/) source separation library with pretrained models
+written in [Python](https://www.python.org/) and uses [Tensorflow](tensorflow.org/). It makes it easy
+to train source separation model (assuming you have a dataset of isolated sources), and provides
+already trained state of the art model for performing various flavour of separation :
+
+* Vocals (singing voice) / accompaniment separation ([2 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-2stems-model))
+* Vocals / drums / bass / other separation ([4 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-4stems-model))
+* Vocals / drums / bass / piano / other separation ([5 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-5stems-model))
+
+2 stems and 4 stems models have state of the art performances on the
+[musdb](https://sigsep.github.io/datasets/musdb.html) dataset. It is also very fast as
+it can perform separation of audio files to 4 stems 100x faster than real-time when run on a *GPU*.
+We designed it so you can use it straight from [command line](https://github.com/deezer/spleeter/wiki/2.-Getting-started#usage)
+as well as directly in your own development pipeline as a
+[Python library](https://github.com/deezer/spleeter/wiki/4.-API-Reference#separator)
+
+**Spleeter** can be installed with [Conda](https://github.com/deezer/spleeter/wiki/1.-Installation#using-conda),
+with [pip](https://github.com/deezer/spleeter/wiki/1.-Installation#using-pip) or be used with
+[Docker](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-docker-image).
+
+## Quick start 
+
+Want to try it out ? Just clone the repository and install a
+[Conda](https://github.com/deezer/spleeter/wiki/1.-Installation#using-conda)
+environment to start separating audio file as follows:
+
+```bash
+$ git clone https://github.com/Deezer/spleeter
+$ conda env create -f spleeter/conda/spleeter-cpu.yaml
+$ conda activate spleeter-cpu
+$ spleeter separate -i spleeter/audio_example.mp3 -p spleeter:2stems -o output
+```
+You should get two separated audio files (`vocals.wav` and `accompaniment.wav`)
+in the `output/audio_example` folder.
+
+For a more detailed documentation, please check the [repository wiki](https://github.com/deezer/spleeter/wiki)
+
+## Reference
+If you use **Spleeter** in your work, please cite:
+
+```
+@misc{spleeter2019,
+  title={Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models},
+  author={Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
+  howpublished={Late-Breaking/Demo ISMIR 2019},
+  month={November},
+  year={2019}
+}
+```
+
+## License
+The code of **Spleeter** is MIT-licensed.
+
+## Note
+This repository include a demo audio file `audio_example.mp3` which is an excerpt
+from Slow Motion Dream by Steven M Bryant (c) copyright 2011 Licensed under a Creative
+Commons Attribution (3.0) license. http://dig.ccmixter.org/files/stevieb357/34740
+Ft: CSoul,Alex Beroza & Robert Siekawitch

conda/spleeter-cpu.yaml

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+name: spleeter-cpu
+
+channels:
+  - conda-forge
+  - anaconda
+
+dependencies:
+  - python=3.7
+  - tensorflow=1.14.0
+  - ffmpeg
+  - pandas==0.25.1
+  - requests
+  - pip
+  - pip:
+    - museval==0.3.0
+    - musdb==0.3.1
+    - norbert==0.2.1
+    - spleeter

conda/spleeter-gpu.yaml

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+name: spleeter-gpu
+
+channels:
+  - conda-forge
+  - anaconda
+
+dependencies:
+  - python=3.7
+  - tensorflow-gpu=1.14.0
+  - ffmpeg
+  - pandas==0.25.1
+  - requests
+  - pip
+  - pip:
+    - museval==0.3.0
+    - musdb==0.3.1
+    - norbert==0.2.1
+    - spleeter
+

configs/2stems/base_config.json

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+{
+    "train_csv": "path/to/train.csv",
+    "validation_csv": "path/to/test.csv",
+    "model_dir": "2stems",
+    "mix_name": "mix",
+    "instrument_list": ["vocals", "accompaniment"],
+    "sample_rate":44100,
+    "frame_length":4096,
+    "frame_step":1024,
+    "T":512,
+    "F":1024,
+    "n_channels":2,
+    "separation_exponent":2,
+    "mask_extension":"zeros",
+    "learning_rate": 1e-4,
+    "batch_size":4,
+    "training_cache":"training_cache",
+    "validation_cache":"validation_cache",
+    "train_max_steps": 1000000,
+    "throttle_secs":300,
+    "random_seed":0,
+    "save_checkpoints_steps":150,
+    "save_summary_steps":5,
+    "model":{
+            "type":"unet.unet",
+            "params":{}
+            }
+}

configs/4stems/base_config.json

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+{
+    "train_csv": "path/to/train.csv",
+    "validation_csv": "path/to/test.csv",
+    "model_dir": "4stems",
+    "mix_name": "mix",
+    "instrument_list": ["vocals", "drums", "bass", "other"],
+    "sample_rate":44100,
+    "frame_length":4096,
+    "frame_step":1024,
+    "T":512,
+    "F":1024,
+    "n_channels":2,
+    "separation_exponent":2,
+    "mask_extension":"zeros",
+    "learning_rate": 1e-4,
+    "batch_size":4,
+    "training_cache":"training_cache",
+    "validation_cache":"validation_cache",
+    "train_max_steps": 1500000,
+    "throttle_secs":600,
+    "random_seed":3,
+    "save_checkpoints_steps":300,
+    "save_summary_steps":5,
+    "model":{
+        "type":"unet.unet",
+        "params":{
+               "conv_activation":"ELU",
+               "deconv_activation":"ELU"
+        }
+    }
+}

configs/5stems/base_config.json

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+{
+    "train_csv": "path/to/train.csv",
+    "validation_csv": "path/to/test.csv",
+    "model_dir": "5stems",
+    "mix_name": "mix",
+    "instrument_list": ["vocals", "piano", "drums", "bass", "other"],
+    "sample_rate":44100,
+    "frame_length":4096,
+    "frame_step":1024,
+    "T":512,
+    "F":1024,
+    "n_channels":2,
+    "separation_exponent":2,
+    "mask_extension":"zeros",
+    "learning_rate": 1e-4,
+    "batch_size":4,
+    "training_cache":"training_cache",
+    "validation_cache":"validation_cache",
+    "train_max_steps": 2500000,
+    "throttle_secs":600,
+    "random_seed":8,
+    "save_checkpoints_steps":300,
+    "save_summary_steps":5,
+    "model":{
+        "type":"unet.softmax_unet",
+        "params":{
+               "conv_activation":"ELU",
+               "deconv_activation":"ELU"
+        }
+    }
+}