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from __future__ import annotations
import logging
import os
import torch
from modules import (
devices,
errors,
face_restoration,
face_restoration_utils,
modelloader,
shared,
)
logger = logging.getLogger(__name__)
model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
model_download_name = "GFPGANv1.4.pth"
gfpgan_face_restorer: face_restoration.FaceRestoration | None = None
class FaceRestorerGFPGAN(face_restoration_utils.CommonFaceRestoration):
def name(self):
return "GFPGAN"
def get_device(self):
return devices.device_gfpgan
def load_net(self) -> torch.Module:
for model_path in modelloader.load_models(
model_path=self.model_path,
model_url=model_url,
command_path=self.model_path,
download_name=model_download_name,
ext_filter=['.pth'],
):
if 'GFPGAN' in os.path.basename(model_path):
model = modelloader.load_spandrel_model(
model_path,
device=self.get_device(),
expected_architecture='GFPGAN',
).model
model.different_w = True # see https://github.com/chaiNNer-org/spandrel/pull/81
return 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)
logger.warning("GFPGAN face restorer 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)
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