main.py

@@ -37,10 +37,9 @@ def plot_two_images(a: np.ndarray, b: np.ndarray):
   plt.show()
 
 
-def compare_with_anime_characters(source: np.ndarray, verbose=False) -> list[dict]:
-  dataset = load_data('data/images')
+def compare_with_anime_characters(source: np.ndarray, anime_faces_dataset: dict, verbose=False) -> list[dict]:
   all_metrics = []
-  for anime_image, label in zip(dataset['values'], dataset['labels']):
+  for anime_image, label in zip(anime_faces_dataset['values'], anime_faces_dataset['labels']):
     current_result = {
       'name': label,
       'metrics': {}
@@ -69,9 +68,32 @@ def transfer_to_anime(img: np.ndarray):
   return algo.cartoonize(img).astype(np.uint8)
 
 
+def validate(test_set, anime_faces_set, metric='correlation'):
+  all_entries = len(test_set['values'])
+  correct = 0
+  for test_image, test_label in zip(test_set['values'], test_set['labels']):
+    output = get_top_results(compare_with_anime_characters(test_image), metric)[0]['name']
+    if output == test_label:
+      correct += 1
+
+  accuracy = correct / all_entries
+  print(f'Accuracy using {metric}: {accuracy * 100}%')
+  return accuracy
+
+
 if __name__ == '__main__':
+  anime_faces_set = load_data('data/images')
+
+  # Uncomment for validation (takes a while)
+  # test_set = load_data('test_set')
+  # validate(test_set, anime_faces_set, 'structural-similarity')
+  # validate(test_set, anime_faces_set, 'euclidean-distance')
+  # validate(test_set, anime_faces_set, 'chi-square')
+  # validate(test_set, anime_faces_set, 'correlation')
+  # validate(test_set, anime_faces_set, 'intersection')
+  # validate(test_set, anime_faces_set, 'bhattacharyya-distance')
   source = load_source('UAM-Andre.jpg')
   source_anime = transfer_to_anime(source)
   source_face_anime = find_and_crop_face(source_anime)
-  results = compare_with_anime_characters(source_face_anime)
+  results = compare_with_anime_characters(source_face_anime, anime_faces_set)
   print(get_top_results(results, count=5))