(self,
                 output_shape,
                 num_input_features=64)
Point Pillar's Scatter.
        Converts learned features from dense tensor to sparse pseudo image. This replaces SECOND's
        second.pytorch.voxelnet.SparseMiddleExtractor.
        :param output_shape: ([int]: 4). Required output shape of features.
        :param num_input_features: <int>. Number of input features.
Point Pillar's Scatter.
        Converts learned features from dense tensor to sparse pseudo image. This replaces SECOND's
        second.pytorch.voxelnet.SparseMiddleExtractor.
        :param output_shape: ([int]: 4). Required output shape of features.
        :param num_input_features: <int>. Number of input features.
Point Pillar s Scatter . Converts learned features from dense tensor to sparse pseudo image . This replaces SECOND s second . pytorch . voxelnet . SparseMiddleExtractor . : param output_shape : ( [ int ] : 4 ) . Required output shape of features . : param num_input_features : <int > . Number of input features .
def __init__(self,
                 output_shape,
                 num_input_features=64):
        """
        Point Pillar's Scatter.
        Converts learned features from dense tensor to sparse pseudo image. This replaces SECOND's
        second.pytorch.voxelnet.SparseMiddleExtractor.
        :param output_shape: ([int]: 4). Required output shape of features.
        :param num_input_features: <int>. Number of input features.
        """

        super().__init__()
        self.name = 'PointPillarsScatter'
        self.output_shape = output_shape
        self.ny = output_shape[2]
        self.nx = output_shape[3]
        self.nchannels = num_input_features
def __init__ ( self , output_shape , num_input_features = 64 ) : super ( ) . __init__ ( ) self . name = 'PointPillarsScatter' self . output_shape = output_shape self . ny = output_shape [ 2 ] self . nx = output_shape [ 3 ] self . nchannels = num_input_features