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32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
import torch
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from copy import deepcopy
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from imaginairy.vendored.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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# TODO: clean pretrained model
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load_net = torch.load(model_path, map_location=lambda storage, loc: storage)
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# remove unnecessary 'module.'
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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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