File size: 1,894 Bytes
66c45a4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
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)
|