diff --git a/src/neural_network/database.py b/src/neural_network/database.py
index 72e6a4f..8f25f93 100644
--- a/src/neural_network/database.py
+++ b/src/neural_network/database.py
@@ -18,9 +18,8 @@ def create_training_data():
 		category_index = CATEGORIES.index(category)
 		for img in os.listdir(path):
 			try:
-				img = np.reshape(img,(-1,28))
 				img_array = cv2.imread(os.path.join(path,img), cv2.IMREAD_GRAYSCALE)
-				new_array = np.reshape(img_array, (-1, 28))
+				new_array = cv2.resize(img_array, (IMG_SIZE,IMG_SIZE))
 				training_data_label.append(category_index)
 				training_data_images.append(new_array)
 			except Exception as e:
diff --git a/src/neural_network/learning_neural_network.py b/src/neural_network/learning_neural_network.py
index 1f503ef..213ffef 100644
--- a/src/neural_network/learning_neural_network.py
+++ b/src/neural_network/learning_neural_network.py
@@ -43,7 +43,7 @@ if __name__ == '__main__':
 	train(model, 100)
 	
 	# def accuracy(expected, predicted):
-	# 	return len([_ for e, p in zip(expected, predicted) if e == p]) / len(expected)
+	# 	return len([1 for e, p in zip(expected, predicted) if e == p]) / len(expected)
 	#
 	#
 	# predicted = [model(image).argmax() for image in train_images]