cleanup

sagerpascal · Nov 9, 2023 · bdd18e7 · bdd18e7
1 parent f003c7f
commit bdd18e7
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Showing 3 changed files with 34 additions and 34 deletions.
diff --git a/configs/data.yaml b/configs/data.yaml
@@ -49,21 +49,21 @@ mnist:
     train: False
     download: True
 
-  mnist-subset:
-    dir: mnist/
-    beton_dir: beton/mnist/
-    mean: [ 0.1307 ]
-    std: [ 0.3081 ]
-    num_classes: 10
-    num_channels: 1
-    img_width: 28
-    img_height: 28
-    train_dataset_params:
-      train: True
-      download: True
-    test_dataset_params:
-      train: False
-      download: True
+mnist-subset:
+  dir: mnist/
+  beton_dir: beton/mnist/
+  mean: [ 0.1307 ]
+  std: [ 0.3081 ]
+  num_classes: 10
+  num_channels: 1
+  img_width: 28
+  img_height: 28
+  train_dataset_params:
+    train: True
+    download: True
+  test_dataset_params:
+    train: False
+    download: True
 
 imagenet:
   dir: imagenet/
@@ -132,7 +132,7 @@ straightline:
     split: "test"
     vertical_horizontal_only: False
     aug_range: 0
-    num_images: 4
+    num_images: 8
     num_aug_versions: 0
     noise: 0.0
 

diff --git a/src/data/custom_datasets/straight_line.py b/src/data/custom_datasets/straight_line.py
@@ -1,6 +1,7 @@
 import random
 from typing import Callable, List, Literal, Optional, Tuple
 
+import math
 import numpy as np
 import torch
 from PIL import Image, ImageDraw
@@ -276,17 +277,16 @@ def _plot_some_samples():
         transforms.ToTensor(),
     ])
 
-    dataset = StraightLine(split="test", img_h=32, img_w=32, num_images=12, num_aug_versions=9, num_channels=1,
-                           transform=transform, vertical_horizontal_only=True, noise=0.00,
-                           aug_strategy='trajectory', aug_range=15, n_black_pixels=5)
+    dataset = StraightLine(split="train", num_images=8, num_aug_versions=0, num_channels=1,
+                           transform=transform, vertical_horizontal_only=False, noise=0.00)
 
-    fig, axs = plt.subplots(12, 10, figsize=(10, 12))
-    for i in range(12):
+    fig, axs = plt.subplots(1, 8, figsize=(16, 2))
+    for i in range(8):
         img, meta = dataset.get_item(i, n_black_pixels=0)
-        for idx in range(img.shape[0]):
-            j = i * 10 + idx
-            axs[j // 10, j % 10].imshow(img[idx].squeeze(), vmin=0, vmax=1, cmap='gray')
-            axs[j // 10, j % 10].axis('off')
+        alpha = -round(math.atan((meta['line_coords'][1][1]-meta['line_coords'][0][1]) / (meta['line_coords'][1][0]-meta['line_coords'][0][0])) * 180 / math.pi, 2)
+        axs[i].set_title(f"{alpha:.2f}°")
+        axs[i].imshow(torch.where(img==1, 0, 1).squeeze(), vmin=0, vmax=1.2, cmap='gray')
+        axs[i].axis('off')
     plt.tight_layout()
     plt.show()
 

diff --git a/src/lateral_connections/s1_lateral_connections.py b/src/lateral_connections/s1_lateral_connections.py
@@ -647,15 +647,15 @@ def _plot_lateral_output(img,
                     files.extend([if_fp, am_fp, hm_fp, lo_fp])
                 else:
                     if_fp, am_fp, hm_fp, lo_fp = None, None, None, None
-                if plot_input_features:
-                    _plot_input_features(img_i[batch_idx], features_i[batch_idx], input_features_i[batch_idx],
-                                         fig_fp=if_fp, show_plot=show_plot)
-                elif if_fp is not None:
-                    files.remove(if_fp)
-                _plot_lateral_activation_map(lateral_features_i[batch_idx],
-                                             fig_fp=am_fp, show_plot=show_plot)
-                _plot_lateral_heat_map(lateral_features_f_i[batch_idx],
-                                       fig_fp=hm_fp, show_plot=show_plot)
+                # if plot_input_features:
+                #     _plot_input_features(img_i[batch_idx], features_i[batch_idx], input_features_i[batch_idx],
+                #                          fig_fp=if_fp, show_plot=show_plot)
+                # elif if_fp is not None:
+                #     files.remove(if_fp)
+                # _plot_lateral_activation_map(lateral_features_i[batch_idx],
+                #                              fig_fp=am_fp, show_plot=show_plot)
+                # _plot_lateral_heat_map(lateral_features_f_i[batch_idx],
+                #                        fig_fp=hm_fp, show_plot=show_plot)
                 _plot_lateral_output(img_i[batch_idx], lateral_features_i[batch_idx],
                                      fig_fp=lo_fp, show_plot=show_plot)