from __future__ import annotations

import torch
import os

from modules import (
    devices,
    errors,
    face_restoration,
    face_restoration_utils,
    modelloader,
    shared,
)

gfpgan_face_restorer: face_restoration.FaceRestoration | None = None


class FaceRestorerGFPGAN(face_restoration_utils.CommonFaceRestoration):
    def name(self):
        return "GFPGAN"

    def load_net(self) -> torch.nn.Module:
        os.makedirs(self.model_path, exist_ok=True)
        for model_path in modelloader.load_models(
            model_path=self.model_path,
            model_url="https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth",
            command_path=self.model_path,
            download_name="GFPGANv1.4.pth",
            ext_filter=[".pth"],
        ):
            return modelloader.load_spandrel_model(
                model_path,
                device=devices.device_gfpgan,
                expected_architecture="GFPGAN",
            ).model
        raise ValueError("No GFPGAN Model Found")

    def restore(self, np_image):
        def restore_face(cropped_face_t):
            assert self.net is not None
            return self.net(cropped_face_t, return_rgb=False)[0]

        return self.restore_with_helper(np_image, restore_face)


def gfpgan_fix_faces(np_image):
    if gfpgan_face_restorer:
        return gfpgan_face_restorer.restore(np_image)
    print("WARNING: GFPGAN face restorer was not set up")
    return np_image


def setup_model(dirname: str) -> None:
    global gfpgan_face_restorer

    try:
        face_restoration_utils.patch_facexlib(dirname)
        gfpgan_face_restorer = FaceRestorerGFPGAN(model_path=dirname)
        shared.face_restorers.append(gfpgan_face_restorer)
    except Exception:
        errors.report("Error setting up GFPGAN", exc_info=True)