def create_input(self, t_input=None, forget_xy_shape=True):
"""Create input tensor."""
if t_input is None:
t_input = tf.placeholder(tf.float32, self.image_shape)
t_prep_input = t_input
if len(t_prep_input.shape) == 3:
t_prep_input = tf.expand_dims(t_prep_input, 0)
if forget_xy_shape:
t_prep_input = forget_xy(t_prep_input)
lo, hi = self.image_value_range
t_prep_input = lo + t_prep_input * (hi - lo)
return t_input, t_prep_input
def create_input(self, t_input=None, forget_xy_shape=True):
"""Create input tensor."""
if t_input is None:
t_input = tf.placeholder(tf.float32, self.image_shape)
t_prep_input = t_input
if len(t_prep_input.shape) == 3:
t_prep_input = tf.expand_dims(t_prep_input, 0)
if forget_xy_shape:
t_prep_input = model_util.forget_xy(t_prep_input)
if hasattr(self, "is_BGR") and self.is_BGR is True:
t_prep_input = tf.reverse(t_prep_input, [-1])
lo, hi = self.image_value_range
t_prep_input = lo + t_prep_input * (hi - lo)
return t_input, t_prep_input