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Set device for facelib/facexlib and gfpgan 

* FaceXLib/FaceLib doesn't pass the device argument to RetinaFace but instead chooses one itself and sets it to a global - in order to use a device other than its internally chosen default it is necessary to manually replace the default value
* The GFPGAN constructor needs the device argument to work with MPS or a CUDA device ID that differs from the default
This commit is contained in:
brkirch 2022-11-07 20:12:31 -05:00
parent 804d9fb83d
commit f4a488f585
2 changed files with 6 additions and 1 deletions
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3
modules/codeformer_model.py
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@ -36,6 +36,7 @@ def setup_model(dirname):
from basicsr.utils.download_util import load_file_from_url from basicsr.utils.download_util import load_file_from_url
from basicsr.utils import imwrite, img2tensor, tensor2img from basicsr.utils import imwrite, img2tensor, tensor2img
from facelib.utils.face_restoration_helper import FaceRestoreHelper from facelib.utils.face_restoration_helper import FaceRestoreHelper
from facelib.detection.retinaface import retinaface
from modules.shared import cmd_opts from modules.shared import cmd_opts
net_class = CodeFormer net_class = CodeFormer
@ -65,6 +66,8 @@ def setup_model(dirname):
net.load_state_dict(checkpoint) net.load_state_dict(checkpoint)
net.eval() net.eval()
if hasattr(retinaface, 'device'):
retinaface.device = devices.device_codeformer
face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=devices.device_codeformer) face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=devices.device_codeformer)
self.net = net self.net = net

4
modules/gfpgan_model.py
View File

@ -36,7 +36,9 @@ def gfpgann():
else: else:
print("Unable to load gfpgan model!") print("Unable to load gfpgan model!")
return None return None
model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=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 loaded_gfpgan_model = model
return model return model