pose_model.py 文件源码

def _meshgrid(self, height, width):
    with tf.variable_scope('_meshgrid'):
      # This should be equivalent to:
      #  x_t, y_t = np.meshgrid(np.linspace(-1, 1, width),
      #                         np.linspace(-1, 1, height))
      #  ones = np.ones(np.prod(x_t.shape))
      #  grid = np.vstack([x_t.flatten(), y_t.flatten(), ones])
      x_t = tf.matmul(tf.ones(shape=tf.pack([height, 1])),
                        tf.transpose(tf.expand_dims(tf.linspace(-1.0, 1.0, width), 1), [1, 0]))
      y_t = tf.matmul(tf.expand_dims(tf.linspace(-1.0, 1.0, height), 1),
                        tf.ones(shape=tf.pack([1, width])))

      x_t_flat = tf.reshape(x_t, (1, -1))
      y_t_flat = tf.reshape(y_t, (1, -1))

      ones = tf.ones_like(x_t_flat)
      grid = tf.concat(0, [x_t_flat, y_t_flat, ones])
      return grid