--- a
+++ b/hands-on-session-2/utils.py
@@ -0,0 +1,57 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def show_inline(image, title=''):
+    f, ax = plt.subplots(1, 1, figsize=(10,10))
+    ax.grid(False)
+    ax.set_xticks([])
+    ax.set_yticks([])
+    ax.imshow(image)
+    ax.set_title(title)
+    plt.show()
+
+
+def get_patches(out, k, patch_size=36, random=False):
+    image = out['image']
+    graph = out['graph']
+
+    if random:
+        importance_scores = np.random.uniform(size=out['importance_scores'].size)
+    else:
+        importance_scores = out['importance_scores']
+
+    image = np.pad(image,
+                   ((patch_size, patch_size), (patch_size, patch_size), (0, 0)),
+                   mode="constant",
+                   constant_values=255)
+    important_indices = (-importance_scores).argsort()[:k]
+    important_centroids = graph.ndata['centroid'][important_indices, :].cpu().numpy().astype(int)
+
+    patches = []
+    for i in range(k):
+        x, y = important_centroids[i] + patch_size
+        patch = image[y - int(patch_size / 2): y + int(patch_size / 2),
+                x - int(patch_size / 2): x + int(patch_size / 2),
+                :]
+        patches.append(patch)
+    return patches
+
+
+def plot_patches(patches, ncol=5, patch_size=36):
+    nrow = len(patches) // ncol
+    patches = np.stack(patches, axis=0)
+    patches = np.reshape(patches, newshape=(nrow, ncol, patch_size, patch_size, 3))
+
+    for i in range(nrow):
+        for j in range(ncol):
+            if j == 0:
+                grid_ = patches[i, j]
+            else:
+                grid_ = np.hstack((grid_, patches[i, j]))
+        if i == 0:
+            grid = grid_
+        else:
+            grid = np.vstack((grid, grid_))
+
+    show_inline(grid)
\ No newline at end of file