import os

from installer import install
from modules import paths, shared, devices, modelloader, errors

model_dir = "GFPGAN"
user_path = None
model_path = os.path.join(paths.models_path, model_dir)
model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
have_gfpgan = False
loaded_gfpgan_model = None


def gfpgann():
    import facexlib
    import gfpgan # pylint: disable=unused-import
    global loaded_gfpgan_model # pylint: disable=global-statement
    if loaded_gfpgan_model is not None:
        loaded_gfpgan_model.gfpgan.to(devices.device_gfpgan)
        return loaded_gfpgan_model
    if gfpgan_constructor is None:
        return None
    models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN")
    if len(models) == 1 and "http" in models[0]:
        model_file = models[0]
    elif len(models) != 0:
        latest_file = max(models, key=os.path.getctime)
        model_file = latest_file
    else:
        shared.log.error(f"Model failed loading: type=GFPGAN model={model_file}")
        return None
    if hasattr(facexlib.detection.retinaface, 'device'):
        facexlib.detection.retinaface.device = devices.device_gfpgan
    model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None, device=devices.device_gfpgan)
    loaded_gfpgan_model = model
    shared.log.info(f"Model loaded: type=GFPGAN model={model_file}")
    return model


def send_model_to(model, device):
    model.gfpgan.to(device)
    model.face_helper.face_det.to(device)
    model.face_helper.face_parse.to(device)


def gfpgan_fix_faces(np_image):
    model = gfpgann()
    if model is None:
        return np_image

    send_model_to(model, devices.device_gfpgan)

    np_image_bgr = np_image[:, :, ::-1]
    _cropped_faces, _restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
    np_image = gfpgan_output_bgr[:, :, ::-1]

    model.face_helper.clean_all()

    if shared.opts.face_restoration_unload:
        send_model_to(model, devices.cpu)

    return np_image


gfpgan_constructor = None


def setup_model(dirname):
    try:
        if not os.path.exists(model_path):
            os.makedirs(model_path)
    except Exception:
        pass
    try:
        install('basicsr')
        install('gfpgan')
        import gfpgan
        import facexlib
        import modules.face_restoration

        global user_path # pylint: disable=global-statement
        global have_gfpgan # pylint: disable=global-statement
        global gfpgan_constructor # pylint: disable=global-statement
        load_file_from_url_orig = gfpgan.utils.load_file_from_url
        facex_load_file_from_url_orig = facexlib.detection.load_file_from_url
        facex_load_file_from_url_orig2 = facexlib.parsing.load_file_from_url

        def my_load_file_from_url(**kwargs):
            return load_file_from_url_orig(**dict(kwargs, model_dir=model_path))

        def facex_load_file_from_url(**kwargs):
            return facex_load_file_from_url_orig(**dict(kwargs, save_dir=model_path, model_dir=None))

        def facex_load_file_from_url2(**kwargs):
            return facex_load_file_from_url_orig2(**dict(kwargs, save_dir=model_path, model_dir=None))

        gfpgan.utils.load_file_from_url = my_load_file_from_url
        facexlib.detection.load_file_from_url = facex_load_file_from_url
        facexlib.parsing.load_file_from_url = facex_load_file_from_url2
        user_path = dirname
        have_gfpgan = True
        gfpgan_constructor = gfpgan.GFPGANer

        class FaceRestorerGFPGAN(modules.face_restoration.FaceRestoration):
            def name(self):
                return "GFPGAN"

            def restore(self, np_image, p=None): # pylint: disable=unused-argument
                return gfpgan_fix_faces(np_image)

        shared.face_restorers.append(FaceRestorerGFPGAN())
    except Exception as e:
        errors.log.error(f'GFPGan failed to initialize: {e}')