import os import facexlib import gfpgan import modules.face_restoration from modules import paths, shared, devices, modelloader, errors model_dir = "GFPGAN" user_path = None model_path = os.path.join(paths.models_path, model_dir) model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth" have_gfpgan = False loaded_gfpgan_model = None def gfpgann(): global loaded_gfpgan_model global model_path if loaded_gfpgan_model is not None: loaded_gfpgan_model.gfpgan.to(devices.device_gfpgan) return loaded_gfpgan_model if gfpgan_constructor is None: return None models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN") if len(models) == 1 and "http" in models[0]: model_file = models[0] elif len(models) != 0: latest_file = max(models, key=os.path.getctime) model_file = latest_file else: print("Unable to load gfpgan model!") return 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 def send_model_to(model, device): model.gfpgan.to(device) model.face_helper.face_det.to(device) model.face_helper.face_parse.to(device) def gfpgan_fix_faces(np_image): model = gfpgann() if model is None: return np_image send_model_to(model, devices.device_gfpgan) np_image_bgr = np_image[:, :, ::-1] cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True) np_image = gfpgan_output_bgr[:, :, ::-1] model.face_helper.clean_all() if shared.opts.face_restoration_unload: send_model_to(model, devices.cpu) return np_image gfpgan_constructor = None def setup_model(dirname): try: os.makedirs(model_path, exist_ok=True) from gfpgan import GFPGANer from facexlib import detection, parsing # noqa: F401 global user_path global have_gfpgan global gfpgan_constructor 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 have_gfpgan = True gfpgan_constructor = GFPGANer class FaceRestorerGFPGAN(modules.face_restoration.FaceRestoration): def name(self): return "GFPGAN" def restore(self, np_image): return gfpgan_fix_faces(np_image) shared.face_restorers.append(FaceRestorerGFPGAN()) except Exception: errors.report("Error setting up GFPGAN", exc_info=True)