Fix and reenable summary outputs.

diff --git a/voxel_flow_train.py b/voxel_flow_train.py
index 4440e798410e9ec4b16f638146a5d4fcf8862be4..6b2bcb440a7598a5cdda25ca76ab8a1e70b4b44b 100755 (executable)
--- a/voxel_flow_train.py
+++ b/voxel_flow_train.py
@@ -71,7 +71,8 @@ def train(dataset_frame1, dataset_frame2, dataset_frame3):
     summaries.append(tf.summary.scalar('total_loss', total_loss))
     summaries.append(tf.summary.scalar('reproduction_loss', reproduction_loss))
     # summaries.append(tf.summary.scalar('prior_loss', prior_loss))
-    summaries.append(tf.summary.image('Input Image', input_placeholder, 3))
+    summaries.append(tf.summary.image('Input Image (before)', input_placeholder[:, :, :, 0:3], 3));
+    summaries.append(tf.summary.image('Input Image (after)', input_placeholder[:, :, :, 3:6], 3));
     summaries.append(tf.summary.image('Output Image', prediction, 3))
     summaries.append(tf.summary.image('Target Image', target_placeholder, 3))
 
@@ -149,11 +150,13 @@ def train(dataset_frame1, dataset_frame2, dataset_frame3):
         shuffle(data_list_frame3)
         print('Epoch Number: %d' % int(step / epoch_num))
       
-      # Output Summary 
       if step % 10 == 0:
-        # summary_str = sess.run(summary_op, feed_dict = feed_dict)
-        # summary_writer.add_summary(summary_str, step)
-             print("Loss at step %d: %f" % (step, loss_value))
+        print("Loss at step %d: %f" % (step, loss_value))
+
+      if step % 100 == 0:
+        # Output Summary 
+        summary_str = sess.run(summary_op, feed_dict = feed_dict)
+        summary_writer.add_summary(summary_str, step)
 
       if step % 500 == 0:
         # Run a batch of images