artifactbench/pyproject.toml at main · Intrect-io/artifactbench · GitHub

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[build-system]
requires = ["setuptools>=68", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "artifactbench"
version = "0.2.0"
description = "Benchmark runner for AI-generated music detection (ArtifactNet, CLAM, SpecTTTra)"
readme = "README.md"
requires-python = ">=3.10"
license = { text = "MIT" }
authors = [{ name = "Intrect", email = "contact@intrect.io" }]
keywords = ["audio", "benchmark", "ai-music-detection", "forensic"]
classifiers = [
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Multimedia :: Sound/Audio :: Analysis",
]
dependencies = [
    "numpy>=1.24",
    "torch>=2.0",
    "torchaudio>=2.0",
    "soundfile>=0.12",
    "onnxruntime>=1.17",
    "huggingface_hub>=0.25",
    "matplotlib>=3.7",
    "scikit-learn>=1.3",
    "scipy>=1.10",
    "soxr>=0.3.7",
]

[project.optional-dependencies]
clam = ["transformers>=4.40"]
spectttra = [
    "sonics @ git+https://github.com/awsaf49/sonics.git@9156ffad151f797c71556923c4a02fa01fa8fc91",
]

[project.urls]
Homepage = "https://github.com/Intrect-io/artifactbench"
Dataset  = "https://huggingface.co/datasets/intrect/artifactbench"
Model    = "https://huggingface.co/intrect/artifactnet"
Paper    = "https://arxiv.org/abs/2604.16254"

[project.scripts]
artifactbench = "artifactbench.bench:main"

[tool.setuptools.packages.find]
include = ["artifactbench*"]

[tool.pytest.ini_options]
markers = [
    "slow: network, model-loading, or model-inference integration tests",
]