2022-09-03 12:08:45 +03:00
|
|
|
import os
|
|
|
|
|
2022-09-30 01:46:23 +03:00
|
|
|
import facexlib
|
|
|
|
import gfpgan
|
|
|
|
|
2022-09-07 12:32:28 +03:00
|
|
|
import modules.face_restoration
|
2023-05-31 19:56:37 +03:00
|
|
|
from modules import paths, shared, devices, modelloader, errors
|
2022-09-03 12:08:45 +03:00
|
|
|
|
2022-09-26 17:29:50 +03:00
|
|
|
model_dir = "GFPGAN"
|
2022-09-30 01:46:23 +03:00
|
|
|
user_path = None
|
2023-01-25 19:15:42 +03:00
|
|
|
model_path = os.path.join(paths.models_path, model_dir)
|
2022-09-26 17:29:50 +03:00
|
|
|
model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
|
2022-09-30 01:46:23 +03:00
|
|
|
have_gfpgan = False
|
2022-09-03 12:08:45 +03:00
|
|
|
loaded_gfpgan_model = None
|
|
|
|
|
|
|
|
|
2022-09-30 01:46:23 +03:00
|
|
|
def gfpgann():
|
2022-09-03 12:08:45 +03:00
|
|
|
global loaded_gfpgan_model
|
2022-09-26 17:29:50 +03:00
|
|
|
global model_path
|
2022-09-03 17:28:30 +03:00
|
|
|
if loaded_gfpgan_model is not None:
|
2022-10-01 06:53:25 +03:00
|
|
|
loaded_gfpgan_model.gfpgan.to(devices.device_gfpgan)
|
2022-09-03 17:28:30 +03:00
|
|
|
return loaded_gfpgan_model
|
2022-09-03 12:08:45 +03:00
|
|
|
|
2022-09-03 17:28:30 +03:00
|
|
|
if gfpgan_constructor is None:
|
|
|
|
return None
|
|
|
|
|
2022-09-30 01:46:23 +03:00
|
|
|
models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN")
|
2023-05-29 09:41:36 +03:00
|
|
|
if len(models) == 1 and models[0].startswith("http"):
|
2022-09-30 01:46:23 +03:00
|
|
|
model_file = models[0]
|
|
|
|
elif len(models) != 0:
|
2022-09-26 17:29:50 +03:00
|
|
|
latest_file = max(models, key=os.path.getctime)
|
|
|
|
model_file = latest_file
|
|
|
|
else:
|
|
|
|
print("Unable to load gfpgan model!")
|
|
|
|
return None
|
2022-11-08 04:12:31 +03:00
|
|
|
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)
|
2022-09-12 18:40:06 +03:00
|
|
|
loaded_gfpgan_model = model
|
2022-09-03 17:28:30 +03:00
|
|
|
|
|
|
|
return model
|
2022-09-03 12:08:45 +03:00
|
|
|
|
|
|
|
|
2022-10-04 12:32:22 +03:00
|
|
|
def send_model_to(model, device):
|
|
|
|
model.gfpgan.to(device)
|
|
|
|
model.face_helper.face_det.to(device)
|
|
|
|
model.face_helper.face_parse.to(device)
|
|
|
|
|
|
|
|
|
2022-09-03 12:08:45 +03:00
|
|
|
def gfpgan_fix_faces(np_image):
|
2022-09-30 01:46:23 +03:00
|
|
|
model = gfpgann()
|
2022-09-26 17:29:50 +03:00
|
|
|
if model is None:
|
|
|
|
return np_image
|
2022-10-04 12:32:22 +03:00
|
|
|
|
2022-10-04 14:42:53 +03:00
|
|
|
send_model_to(model, devices.device_gfpgan)
|
2022-10-04 12:32:22 +03:00
|
|
|
|
2022-09-03 12:08:45 +03:00
|
|
|
np_image_bgr = np_image[:, :, ::-1]
|
2022-09-30 11:42:40 +03:00
|
|
|
cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
|
2022-09-03 12:08:45 +03:00
|
|
|
np_image = gfpgan_output_bgr[:, :, ::-1]
|
|
|
|
|
2022-10-04 12:32:22 +03:00
|
|
|
model.face_helper.clean_all()
|
|
|
|
|
2022-09-12 18:40:06 +03:00
|
|
|
if shared.opts.face_restoration_unload:
|
2022-10-04 12:32:22 +03:00
|
|
|
send_model_to(model, devices.cpu)
|
2022-09-12 18:40:06 +03:00
|
|
|
|
2022-09-03 12:08:45 +03:00
|
|
|
return np_image
|
|
|
|
|
|
|
|
|
|
|
|
gfpgan_constructor = None
|
|
|
|
|
|
|
|
|
2022-09-26 17:29:50 +03:00
|
|
|
def setup_model(dirname):
|
|
|
|
try:
|
2023-05-29 10:18:15 +03:00
|
|
|
os.makedirs(model_path, exist_ok=True)
|
2022-09-30 01:46:23 +03:00
|
|
|
from gfpgan import GFPGANer
|
2023-05-10 09:02:23 +03:00
|
|
|
from facexlib import detection, parsing # noqa: F401
|
2022-09-30 01:46:23 +03:00
|
|
|
global user_path
|
2022-09-03 12:08:45 +03:00
|
|
|
global have_gfpgan
|
|
|
|
global gfpgan_constructor
|
2022-09-26 17:29:50 +03:00
|
|
|
|
2022-09-30 01:46:23 +03:00
|
|
|
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
|
2022-09-26 17:29:50 +03:00
|
|
|
have_gfpgan = True
|
2022-09-30 01:46:23 +03:00
|
|
|
gfpgan_constructor = GFPGANer
|
2022-09-07 12:32:28 +03:00
|
|
|
|
|
|
|
class FaceRestorerGFPGAN(modules.face_restoration.FaceRestoration):
|
|
|
|
def name(self):
|
|
|
|
return "GFPGAN"
|
|
|
|
|
|
|
|
def restore(self, np_image):
|
2022-10-03 08:53:52 +03:00
|
|
|
return gfpgan_fix_faces(np_image)
|
2022-09-07 12:32:28 +03:00
|
|
|
|
|
|
|
shared.face_restorers.append(FaceRestorerGFPGAN())
|
2022-09-03 12:08:45 +03:00
|
|
|
except Exception:
|
2023-05-31 19:56:37 +03:00
|
|
|
errors.report("Error setting up GFPGAN", exc_info=True)
|