env.py

import os
import sys
import subprocess
import importlib.metadata


def config_env():
    packages_to_install = [
        ('gradio',None),
        ('numpy',None),
        ('tensorflow', '2.9'),
        ('keras', '2.9'),
        ('opencv-python-headless', '4.5.5.64'),
        ('python-dotenv', None),
        ('torch', None),
        ('torchvision', None),
        ('xplique', None),
        ('segment_anything', None),
        ('panopticapi', None),
        ('keras_cv_attention_models',None)
    ]

    name_to_command = {'segment_anything':'git+https://github.com/facebookresearch/segment-anything.git',
                'panopticapi':'git+https://github.com/cocodataset/panopticapi.git',
                }

    env_name = os.path.basename(sys.prefix)
    print(env_name)
    for package, version in packages_to_install:
        package_spec = f"{package}=={version}" if version else package
        package_spec = name_to_command[package_spec] if package_spec in name_to_command else package_spec
        if not is_pkg_installed(package):
            subprocess.call(f"pip install {package_spec}".split()) 
        else:
            print(f"{package_spec} is already installed.")



    #print(os.getenv('SYSTEM'))

    '''
    if os.getenv('SYSTEM') == 'spaces':
        subprocess.call('pip install tensorflow==2.9'.split())
        subprocess.call('pip install keras==2.9'.split())
        subprocess.call('pip install git+https://github.com/facebookresearch/segment-anything.git'.split())
        subprocess.call('pip install opencv-python-headless==4.5.5.64'.split())
        subprocess.call('pip install git+https://github.com/cocodataset/panopticapi.git'.split())
        subprocess.call('pip install python-dotenv'.split())
        subprocess.call('pip install torch torchvision '.split())
        subprocess.call('pip install xplique'.split())
    '''


def is_pkg_installed(pkg_name):
    try:
        importlib.metadata.distribution(pkg_name)
        return True
    except importlib.metadata.PackageNotFoundError:
        return False