Fix dense depth loss and model, fix metric naming

losses.py

@@ -5,6 +5,10 @@ def dense_depth_loss_function(y, y_pred):
     """
     Implementation of the loss from the dense depth paper https://arxiv.org/pdf/1812.11941.pdf
     """
+    if len(y.shape) == 3:
+        y = tf.expand_dims(y, 3)
+    if len(y_pred.shape) == 3:
+        y_pred = tf.expand_dims(y_pred, 3)
     # Point-wise L1 loss
     l1_depth = tf.reduce_mean(tf.math.abs(y_pred - y), axis=-1)
 
@@ -15,6 +19,6 @@ def dense_depth_loss_function(y, y_pred):
                               tf.math.abs(dx_pred - dx), axis=-1)
 
     #  Structural Similarity (SSIM)
-    ssim = (1 - tf.image.ssim(y, y_pred, 500)) / 2
+    ssim = tf.clip_by_value((1 - tf.image.ssim(y, y_pred, 100)) / 2, 0, 1)
 
     return 0.1 * tf.reduce_mean(l1_depth) + tf.reduce_mean(gradient) + ssim