From 84eabfae0e9060bfe108f3ed50180ae0069250d2 Mon Sep 17 00:00:00 2001
From: s486797 <Sarafina1*>
Date: Fri, 23 Aug 2024 15:49:27 +0200
Subject: [PATCH] add terminal notifications

---
 neural_style_app/app.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/neural_style_app/app.py b/neural_style_app/app.py
index d235aea..2b7e92c 100644
--- a/neural_style_app/app.py
+++ b/neural_style_app/app.py
@@ -76,6 +76,7 @@ def visualize():
     conv_layers = []
     for module in pretrained_model.children():
         if isinstance(module, nn.Conv2d):
+            print("Adding module to the layers... ")
             conv_layers.append(module)
 
     # Pass the resulting image through the convolutional layers and capture feature maps
@@ -85,12 +86,14 @@ def visualize():
 
     for i, layer in enumerate(conv_layers):
         input_image = layer(input_image)
+        print("Passing through feature maps - layer " , i)
         feature_maps.append(input_image)
         layer_names.append(f"Layer {i + 1}: {str(layer)}")
 
     # Process and feature maps
     processed_feature_maps = []
     for feature_map in feature_maps:
+        print("Processing feature map...")
         feature_map = feature_map.squeeze(0)  # Remove the batch dimension
         mean_feature_map = torch.mean(feature_map, dim=0).cpu().detach().numpy()  # Compute mean across channels
         processed_feature_maps.append(mean_feature_map)
@@ -98,6 +101,7 @@ def visualize():
     # Plot the feature maps
     fig = plt.figure(figsize=(20, 20))
     for i, fm in enumerate(processed_feature_maps):
+        print("Plotting feature maps... now at map number ", i)
         ax = fig.add_subplot(4, 4, i + 1)  # Adjust grid size as needed
         ax.imshow(fm, cmap='viridis')  # Display feature map as image
         ax.axis("off")