Update data augmentation in the largedataset_cnn example
diff --git a/examples/largedataset_cnn/train_largedata.py b/examples/largedataset_cnn/train_largedata.py
index 2a79675..81f3e72 100644
--- a/examples/largedataset_cnn/train_largedata.py
+++ b/examples/largedataset_cnn/train_largedata.py
@@ -193,7 +193,7 @@
# Generate the patch data in this iteration
x = train_x[idx[b * batch_size:(b + 1) * batch_size]]
x = process_data.paths_to_images(x,model.input_size)
- if model.dimension == 4:
+ if model.dimension == 4: # Move the augmentation outside the for loop for better efficiency
x = augmentation(x, batch_size)
y = train_y[idx[b * batch_size:(b + 1) * batch_size]]
