From 892faa18e4e48e783a31f80aa6f958c68892ab7d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=90=9B=E5=90=9B=E8=87=A3=E8=87=A3=E5=90=9B?= Date: Fri, 30 Sep 2022 05:46:36 +0000 Subject: [PATCH] update examples/community/face_adversarial_attack/test.py. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: 君君臣臣君 --- .../community/face_adversarial_attack/test.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/examples/community/face_adversarial_attack/test.py b/examples/community/face_adversarial_attack/test.py index de483d8..e01df61 100644 --- a/examples/community/face_adversarial_attack/test.py +++ b/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]) @@ -45,9 +45,8 @@ if __name__ == '__main__': 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])))