--- a
+++ b/extra/augmentation.py
@@ -0,0 +1,52 @@
+import SimpleITK as sitk
+import numpy as np
+import torch
+from config.config import *
+from config.paths import train_images_folder, train_labels_folder, train_images, train_labels
+
+transforms_dict = {
+    RandomAffine(): 0.75,
+    RandomElasticDeformation(max_displacement=3): 0.25,
+}
+
+transform = Compose(transforms_dict)
+
+idx = 0
+train_image = train_images[0]
+train_label = train_labels[0]
+
+image_path = os.path.join(train_images_folder, train_image)
+label_path = os.path.join(train_labels_folder, train_label)
+
+image_sitk = sitk.ReadImage(image_path)
+label_sitk = sitk.ReadImage(label_path)
+
+image_np = sitk.GetArrayFromImage(image_sitk)
+label_np = sitk.GetArrayFromImage(label_sitk)
+
+image_np = np.expand_dims(image_np,axis=0)
+label_np = np.expand_dims(label_np,axis=0)
+
+image_np_out = transform(image_np)
+
+image_t = torch.from_numpy(image_np)
+label_t = torch.from_numpy(label_np)
+
+s1 = torchio.Subject(
+    t1    = torchio.Image(type=torchio.INTENSITY, tensor=image_t),
+    label = torchio.Image(type=torchio.LABEL, tensor=label_t),
+)
+out_t = transform(s1)
+
+# +=============================+
+# +  RandomElasticDeformation   +
+# +=============================+
+
+image_sitk.GetSize()
+image_sitk.GetSpacing()
+bounds = np.array(image_sitk.GetSize()) * np.array(image_sitk.GetSpacing())
+num_control_points = np.array((7, 7, 6))
+grid_spacing = bounds / (num_control_points - 2)
+print("Grid Spacing = ", grid_spacing)
+potential_folding = grid_spacing / 2
+print("Potential Folding = ", potential_folding)