diff --git a/tf/categorize.py b/tf/categorize.py
new file mode 100755
index 0000000..7bb3e96
--- /dev/null
+++ b/tf/categorize.py
@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+
+import tensorflow as tf
+import pathlib
+import random
+import matplotlib.pyplot as plt
+
+tf.enable_eager_execution()
+
+
+data_root = pathlib.Path('../img/')
+
+all_image_paths = list(data_root.glob('*/*'))
+all_image_paths = [str(path) for path in all_image_paths]
+random.shuffle(all_image_paths)
+image_count = len(all_image_paths)
+label_names = sorted(item.name for item in data_root.glob('*/') if item.is_dir())
+label_to_index = dict((name, index) for index,name in enumerate(label_names))
+all_image_labels = [label_to_index[pathlib.Path(path).parent.name]
+                    for path in all_image_paths]
+
+def preprocess_image(image):
+  image = tf.image.decode_image(image, channels=3)
+  image = tf.image.resize_images(image, [192, 192])
+  image /= 255.0  # normalize to [0,1] range
+  return image
+
+def load_and_preprocess_image(path):
+  image = tf.read_file(path)
+  return preprocess_image(image)
+
+image_path = all_image_paths[0]
+label = all_image_labels[0]
+
+image = load_and_preprocess_image(image_path)
+plt.imshow(image)
+plt.grid(False)
+plt.title(label_names[label].title())
+print()