| | import torch |
| | from copy import deepcopy |
| |
|
| | from extras.facexlib.utils import load_file_from_url |
| | from .retinaface import RetinaFace |
| |
|
| |
|
| | def init_detection_model(model_name, half=False, device='cuda', model_rootpath=None): |
| | if model_name == 'retinaface_resnet50': |
| | model = RetinaFace(network_name='resnet50', half=half, device=device) |
| | model_url = 'https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth' |
| | elif model_name == 'retinaface_mobile0.25': |
| | model = RetinaFace(network_name='mobile0.25', half=half, device=device) |
| | model_url = 'https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_mobilenet0.25_Final.pth' |
| | else: |
| | raise NotImplementedError(f'{model_name} is not implemented.') |
| |
|
| | model_path = load_file_from_url( |
| | url=model_url, model_dir='facexlib/weights', progress=True, file_name=None, save_dir=model_rootpath) |
| |
|
| | |
| | load_net = torch.load(model_path, map_location=lambda storage, loc: storage) |
| | |
| | for k, v in deepcopy(load_net).items(): |
| | if k.startswith('module.'): |
| | load_net[k[7:]] = v |
| | load_net.pop(k) |
| | model.load_state_dict(load_net, strict=True) |
| | model.eval() |
| | model = model.to(device) |
| | return model |
| |
|
