update examples/community/face_adversarial_attack/test.py.

Signed-off-by: 君君臣臣君 <mingjun@isrc.iscas.ac.cn>

examples/community/face_adversarial_attack/test.py

@@ -21,21 +21,21 @@ from mindspore.dataset.vision.py_transforms import ToTensor
 import mindspore.dataset.vision.py_transforms as P
 from mindspore.dataset.vision.py_transforms import ToPIL as ToPILImage
 from FaceRecognition.eval import get_net
-import AFR
+import adversarial_attack
 
 context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
 
 
-imageize = ToPILImage()
+
 
 if __name__ == '__main__':
     """
     The input image, target image and adversarial image are tested using the FaceRecognition model.
     """
 
-    image = AFR.load_data('photos/adv_input/')
-    inputs = AFR.load_data('photos/input/')
-    targets = AFR.load_data('photos/target/')
+    image = adversarial_attack.load_data('photos/adv_input/')
+    inputs = adversarial_attack.load_data('photos/input/')
+    targets = adversarial_attack.load_data('photos/target/')
 
     tensorize = ToTensor()
     normalize = P.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
@@ -44,10 +44,8 @@ if __name__ == '__main__':
     STD = Tensor([0.229, 0.224, 0.225])
 
     resnet = get_net()
-
-    image = mp.imread("./outputs/adversarial_example.jpg")
-    adv = Tensor(normalize(tensorize(image)))
-
+    
+    adv = Tensor(normalize(tensorize(image[0])))
     input_tensor = Tensor(normalize(tensorize(inputs[0])))
     target_tensor = Tensor(normalize(tensorize(targets[0])))