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