lib/models/patchnet.py [91:119]:
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        return output_dict


def result_selection_by_distance(center, box1, box2, box3):
    disntance = torch.zeros(center.shape[0], 1).cuda()
    disntance[:, 0] = center[:, 2] # select batch dim, make mask shape (B, 1)
    box = box1
    box = torch.where(disntance < 30, box, box2)
    box = torch.where(disntance < 50, box, box3)
    return box


if __name__ == '__main__':
    import yaml
    from lib.helpers.kitti_helper import Kitti_Config
    dataset_config = Kitti_Config()
    cfg = {'name': 'patchnet', 'init': 'xavier', 'threshold_offset': 0.5,
           'patch_size': [32, 32], 'num_heading_bin': 12, 'num_size_cluster': 8,
           'backbone': 'plainnet'}

    input = torch.rand(2, 3, 64, 64)
    one_hot = torch.Tensor(2, 3)

    model = PatchNet(cfg,
                     dataset_config.num_heading_bin,
                     dataset_config.num_size_cluster,
                     dataset_config.mean_size_arr)
    output_dict = model(input, one_hot)
    print (output_dict.keys())
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lib/models/patchnet_pct.py [139:167]:
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        return output_dict


def result_selection_by_distance(center, box1, box2, box3):
    disntance = torch.zeros(center.shape[0], 1).cuda()
    disntance[:, 0] = center[:, 2] # select batch dim, make mask shape (B, 1)
    box = box1
    box = torch.where(disntance < 30, box, box2)
    box = torch.where(disntance < 50, box, box3)
    return box


if __name__ == '__main__':
    import yaml
    from lib.helpers.kitti_helper import Kitti_Config
    dataset_config = Kitti_Config()
    cfg = {'name': 'patchnet', 'init': 'xavier', 'threshold_offset': 0.5,
           'patch_size': [32, 32], 'num_heading_bin': 12, 'num_size_cluster': 8,
           'backbone': 'plainnet'}

    input = torch.rand(2, 3, 64, 64)
    one_hot = torch.Tensor(2, 3)

    model = PatchNet(cfg,
                     dataset_config.num_heading_bin,
                     dataset_config.num_size_cluster,
                     dataset_config.mean_size_arr)
    output_dict = model(input, one_hot)
    print (output_dict.keys())
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