From f4a488f585c09b420dc05199240e68f8fb74337f Mon Sep 17 00:00:00 2001 From: brkirch Date: Mon, 7 Nov 2022 20:12:31 -0500 Subject: [PATCH] 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 --- modules/codeformer_model.py | 3 +++ modules/gfpgan_model.py | 4 +++- 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index e6d9fa4f..ab40d842 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -36,6 +36,7 @@ def setup_model(dirname): from basicsr.utils.download_util import load_file_from_url from basicsr.utils import imwrite, img2tensor, tensor2img from facelib.utils.face_restoration_helper import FaceRestoreHelper + from facelib.detection.retinaface import retinaface from modules.shared import cmd_opts net_class = CodeFormer @@ -65,6 +66,8 @@ def setup_model(dirname): net.load_state_dict(checkpoint) 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) self.net = net diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index a9452dce..1e2dbc32 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -36,7 +36,9 @@ def gfpgann(): else: print("Unable to load gfpgan model!") 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 return model