fix image

1 files changed, 4 insertions, 3 deletions

diff --git a/inversion/image_inversion.py b/inversion/image_inversion.py
index 591f4f7..09dd4e7 100644
--- a/inversion/image_inversion.py
+++ b/inversion/image_inversion.py
@@ -150,9 +150,10 @@ inv_step = tf.get_variable('inv_step', initializer=0, trainable=False)
 
 # Define target image.
 IMG_SHAPE = gen_img.get_shape().as_list()[1:]
-target = tf.get_variable(name='target', dtype=tf.int32,
+target = tf.get_variable(name='target', dtype=tf.float32,  # normally this is the real [0-255]image
                          shape=[BATCH_SIZE,] + IMG_SHAPE)
-target_img = (tf.cast(target, tf.float32) / 255.) * 2.0 - 1. # Norm to [-1, 1].
+# target_img = (tf.cast(target, tf.float32) / 255.) * 2.0 - 1. # Norm to [-1, 1].
+target_img = target
 
 # Custom Gradient for Relus.
 if params.custom_grad_relu:
@@ -282,7 +283,7 @@ if params.decay_lr:
       params.inv_it / params.decay_n, 0.1, staircase=True)
 else:
   lrate = tf.constant(params.lr)
-trained_params = [encoding] if params.fixed_z else [latent]
+trained_params = [encoding] if params.fixed_z else [latent, encoding]
 optimizer = tf.train.AdamOptimizer(learning_rate=lrate, beta1=0.9, beta2=0.999)
 inv_train_op = optimizer.minimize(inv_loss, var_list=trained_params,
                                   global_step=inv_step)