Dense_Transformer_Network.py 文件源码

def _makeT(self,cp):
        with tf.variable_scope('_makeT'): 
            cp = tf.reshape(cp,(-1,2,self.Column_controlP_number*self.Row_controlP_number))
            cp = tf.cast(cp,'float32')       
            N_f = tf.shape(cp)[0]             
            #c_s
            x,y = tf.linspace(-1.,1.,self.Column_controlP_number),tf.linspace(-1.,1.,self.Row_controlP_number)
            x,y = tf.meshgrid(x,y)
            xs,ys = tf.transpose(tf.reshape(x,(-1,1))),tf.transpose(tf.reshape(y,(-1,1)))
            cp_s = tf.concat([xs,ys],0)
            cp_s_trans = tf.transpose(cp_s)
            ##===Compute distance R
            xs_trans,ys_trans = tf.transpose(tf.stack([xs],axis=2),perm=[1,0,2]),tf.transpose(tf.stack([ys],axis=2),perm=[1,0,2])
            xs, xs_trans = tf.meshgrid(xs,xs_trans);ys, ys_trans = tf.meshgrid(ys,ys_trans)
            Rx,Ry = tf.square(tf.subtract(xs,xs_trans)),tf.square(tf.subtract(ys,ys_trans))
            R = tf.add(Rx,Ry) 
            R = tf.multiply(R,tf.log(tf.clip_by_value(R,1e-10,1e+10)))
            ones = tf.ones([tf.multiply(self.Row_controlP_number,self.Column_controlP_number),1],tf.float32)
            ones_trans = tf.transpose(ones)
            zeros = tf.zeros([3,3],tf.float32)
            Deltas1 = tf.concat([ones, cp_s_trans, R],1)
            Deltas2 = tf.concat([ones_trans,cp_s],0)
            Deltas2 = tf.concat([zeros,Deltas2],1)          
            Deltas = tf.concat([Deltas1,Deltas2],0)
            ##get deltas_inv
            Deltas_inv = tf.matrix_inverse(Deltas)
            Deltas_inv = tf.expand_dims(Deltas_inv,0)
            Deltas_inv = tf.reshape(Deltas_inv,[-1])
            Deltas_inv_f = tf.tile(Deltas_inv,tf.stack([N_f]))
            Deltas_inv_f = tf.reshape(Deltas_inv_f,tf.stack([N_f,self.Column_controlP_number*self.Row_controlP_number+3, -1]))
            cp_trans =tf.transpose(cp,perm=[0,2,1])
            zeros_f_In = tf.zeros([N_f,3,2],tf.float32)
            cp = tf.concat([cp_trans,zeros_f_In],1)
            T = tf.transpose(tf.matmul(Deltas_inv_f,cp),[0,2,1])
            return T