tools/data_prepare/patch_data_prepare_val.py [196:214]:
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                                       whitelist=['Car'],
                                       img_height_threshold=25):
    ''' Extract point clouds in frustums extruded from 2D detection boxes.
        Update: Lidar points and 3d boxes are in *rect camera* coord system
            (as that in 3d box label files)

    Input:
        det_filename: string, each line is
            img_path typeid confidence xmin ymin xmax ymax
        split: string, either trianing or testing
        output_filename: string, the name for output .pickle file
        whitelist: a list of strings, object types we are interested in.
        img_height_threshold: int, neglect image with height lower than that.
        lidar_point_threshold: int, neglect frustum with too few points.
    Output:
        None (will write a .pickle file to the disk)
    '''
    data_dir = os.path.join(ROOT_DIR, 'data')
    dataset = KittiDataset(root_dir=data_dir, split=split)
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tools/data_prepare/patch_data_prepare_val.py [353:371]:
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                                       whitelist=['Car'],
                                       img_height_threshold=25):
    ''' Extract point clouds in frustums extruded from 2D detection boxes.
        Update: Lidar points and 3d boxes are in *rect camera* coord system
            (as that in 3d box label files)

    Input:
        det_filename: string, each line is
            img_path typeid confidence xmin ymin xmax ymax
        split: string, either trianing or testing
        output_filename: string, the name for output .pickle file
        whitelist: a list of strings, object types we are interested in.
        img_height_threshold: int, neglect image with height lower than that.
        lidar_point_threshold: int, neglect frustum with too few points.
    Output:
        None (will write a .pickle file to the disk)
    '''
    data_dir = os.path.join(ROOT_DIR, 'data')
    dataset = KittiDataset(root_dir=data_dir, split=split)
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