Dense_Transformer_Networks_3D.py 文件源码

def __init__(self,input_shape,control_points_ratio):
        self.num_batch = input_shape[0]
        self.depth = input_shape[1]
        self.height = input_shape[2]
        self.width = input_shape[3]
        self.num_channels = input_shape[4]
        self.out_height = self.height
        self.out_width = self.width
        self.out_depth = self.depth
        self.X_controlP_number = int(input_shape[3] / \
                                (control_points_ratio))
        self.Y_controlP_number = int(input_shape[2] / \
                                (control_points_ratio))
        self.Z_controlP_number = int(input_shape[1] / \
                                (control_points_ratio))
        init_x = np.linspace(-5,5,self.X_controlP_number)
        init_y = np.linspace(-5,5,self.Y_controlP_number)
        init_z = np.linspace(-5,5,self.Z_controlP_number)
        x_s = np.tile(init_x, [self.Y_controlP_number*self.Z_controlP_number])
        y_s = np.tile(np.repeat(init_y,self.X_controlP_number),[self.Z_controlP_number])
        z_s = np.repeat(init_z,self.X_controlP_number*self.Y_controlP_number)        
        self.initial = np.array([x_s,y_s,z_s])