Update app.py

app.py

@@ -20,8 +20,6 @@ mnist_examples = []
 for digit in range(10):
     idx = np.where(y_test == digit)[0][0]
     mnist_examples.append([x_test[idx]])
-# Resize the examples to 100 by 100
-mnist_examples = [[cv2.resize(example[0], DIMS)] for example in mnist_examples]
 
 # Function to preprocess the image
 def preprocess_image(image):
@@ -100,13 +98,15 @@ epsilon = 0.1  # Tweak epsilon to change the intensity of perturbation
 adversarial_examples = []
 
 for i in range(10):
-    img = tf.convert_to_tensor(test_images[i:i+1])
-    label = test_labels[i:i+1]
-    label = tf.reshape(label, [1, 1])
-
+    img = tf.convert_to_tensor(mnist_examples[i][0])
+    label = tf.reshape(tf.convert_to_tensor([i]), [1, 1])
     perturbations = create_adversarial_pattern(img, label)
     adv_x = fgsm_attack(img, epsilon, perturbations)
     adversarial_examples.append([cv2.resize(adv_x.numpy().squeeze(), DIMS)])
+    
+# Resize the examples to 100 by 100
+mnist_examples = [[cv2.resize(example[0], DIMS)] for example in mnist_examples]
+
 
 class GradioInterface:
     def __init__(self):