"""
VintageGAN Package Setup

Installation script for VintageGAN project.

Author: VintageGAN Project
Date: 2024
"""

from setuptools import setup, find_packages
from pathlib import Path

# Read README for long description
readme_file = Path(__file__).parent / "README.md"
long_description = (
    readme_file.read_text(encoding="utf-8") if readme_file.exists() else ""
)

# Read requirements
requirements_file = Path(__file__).parent / "requirements.txt"
requirements = []
if requirements_file.exists():
    with open(requirements_file, "r") as f:
        requirements = [
            line.strip() for line in f if line.strip() and not line.startswith("#")
        ]

setup(
    name="vintagegan",
    version="0.2.0",
    author="VintageGAN Project",
    author_email="",
    description="Controllable vintage image synthesis with conditional GANs",
    long_description=long_description,
    long_description_content_type="text/markdown",
    url="https://github.com/msrishav-28/vintage-gan",
    packages=find_packages(
        exclude=["tests", "notebooks", "data", "checkpoints", "logs", "outputs"]
    ),
    classifiers=[
        "Development Status :: 3 - Alpha",
        "Intended Audience :: Science/Research",
        "Intended Audience :: Developers",
        "License :: OSI Approved :: MIT License",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Image Processing",
    ],
    python_requires=">=3.9",
    install_requires=requirements,
    extras_require={
        "dev": [
            "pytest>=7.0.0",
            "black>=22.0.0",
            "flake8>=4.0.0",
            "mypy>=0.950",
        ],
        "notebook": [
            "jupyter>=1.0.0",
            "ipywidgets>=7.6.0",
        ],
    },
    entry_points={
        "console_scripts": [
            "vintagegan-filter=inference.apply_filter:main",
            "vintagegan-batch=inference.batch_process:main",
            "vintagegan-pretrain=training.pretrain:main",
            "vintagegan-train=training.gan_train:main",
            "vintagegan-ablation=evaluation.ablation:main",
        ],
    },
    include_package_data=True,
    zip_safe=False,
)