def __init__(self, args): torch.manual_seed(317) self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") heads = {'hm': args.num_classes, # cen, tl, tr, bl, br 'reg': 2*args.num_classes, 'wh': 2*4, 'mid_point': 2 * args.num_classes, } self.model = spinal_net.SpineNet(heads=heads, pretrained=True, down_ratio=args.down_ratio, final_kernel=1, head_conv=256) self.num_classes = args.num_classes self.decoder = decoder.DecDecoder(K=args.K, conf_thresh=args.conf_thresh) self.dataset = {'spinal': BaseDataset}
def __init__(self): torch.manual_seed(317) self.device = torch.device( "cuda:0" if torch.cuda.is_available() else "cpu") heads = { 'hm': 1, 'reg': 2, 'wh': 2 * 4, } self.model_path = "model_last.pth" self.model = spinal_net.SpineNet(heads=heads, basename='resnet34', pretrained=True, down_ratio=4, final_kernel=1, head_conv=256) self.down_ratio = 4 self.model_state = False self.decoder = decoder.DecDecoder(K=100, conf_thresh=0.2)