├── README.md ├── deepfool ├── __pycache__ │ └── deepfool_tf.cpython-35.pyc ├── deepfool_sim.py ├── deepfool_tf.py ├── hacked.png ├── mnist_model.py ├── testSample │ ├── img_1.jpg │ ├── img_10.jpg │ ├── img_100.jpg │ ├── img_101.jpg │ ├── img_102.jpg │ ├── img_103.jpg │ ├── img_104.jpg │ ├── img_105.jpg │ ├── img_106.jpg │ ├── img_107.jpg │ ├── img_108.jpg │ ├── img_109.jpg │ ├── img_11.jpg │ ├── img_110.jpg │ ├── img_111.jpg │ ├── img_112.jpg │ ├── img_113.jpg │ ├── img_114.jpg │ ├── img_115.jpg │ ├── img_116.jpg │ ├── img_117.jpg │ ├── img_118.jpg │ ├── img_119.jpg │ ├── img_12.jpg │ ├── img_120.jpg │ ├── img_121.jpg │ ├── img_122.jpg │ ├── img_123.jpg │ ├── img_124.jpg │ ├── img_125.jpg │ ├── img_126.jpg │ ├── img_127.jpg │ ├── img_128.jpg │ ├── img_129.jpg │ ├── img_13.jpg │ ├── img_130.jpg │ ├── img_131.jpg │ ├── img_132.jpg │ ├── img_133.jpg │ ├── img_134.jpg │ ├── img_135.jpg │ ├── img_136.jpg │ ├── img_137.jpg │ ├── img_138.jpg │ ├── img_139.jpg │ ├── img_14.jpg │ ├── img_140.jpg │ ├── img_141.jpg │ ├── img_142.jpg │ ├── img_143.jpg │ ├── img_144.jpg │ ├── img_145.jpg │ ├── img_146.jpg │ ├── img_147.jpg │ ├── img_148.jpg │ ├── img_149.jpg │ ├── img_15.jpg │ ├── img_150.jpg │ ├── img_151.jpg │ ├── img_152.jpg │ ├── img_153.jpg │ ├── img_154.jpg │ ├── img_155.jpg │ ├── img_156.jpg │ ├── img_157.jpg │ ├── img_158.jpg │ ├── img_159.jpg │ ├── img_16.jpg │ ├── img_160.jpg │ ├── img_161.jpg │ ├── img_162.jpg │ ├── img_163.jpg │ ├── img_164.jpg │ ├── img_165.jpg │ ├── img_166.jpg │ ├── img_167.jpg │ ├── img_168.jpg │ ├── img_169.jpg │ ├── img_17.jpg │ ├── img_170.jpg │ ├── img_171.jpg │ ├── img_172.jpg │ ├── img_173.jpg │ ├── img_174.jpg │ ├── img_175.jpg │ ├── img_176.jpg │ ├── img_177.jpg │ ├── img_178.jpg │ ├── img_179.jpg │ ├── img_18.jpg │ ├── img_180.jpg │ ├── img_181.jpg │ ├── img_182.jpg │ ├── img_183.jpg │ ├── img_184.jpg │ ├── img_185.jpg │ ├── img_186.jpg │ ├── img_187.jpg │ ├── img_188.jpg │ ├── img_189.jpg │ ├── img_19.jpg │ ├── img_190.jpg │ ├── img_191.jpg │ ├── img_192.jpg │ ├── img_193.jpg │ ├── img_194.jpg │ ├── img_195.jpg │ ├── img_196.jpg │ ├── img_197.jpg │ ├── img_198.jpg │ ├── img_199.jpg │ ├── img_2.jpg │ ├── img_20.jpg │ ├── img_200.jpg │ ├── img_201.jpg │ ├── img_202.jpg │ ├── img_203.jpg │ ├── img_204.jpg │ ├── img_205.jpg │ ├── img_206.jpg │ ├── img_207.jpg │ ├── img_208.jpg │ ├── img_209.jpg │ ├── img_21.jpg │ ├── img_210.jpg │ ├── img_211.jpg │ ├── img_212.jpg │ ├── img_213.jpg │ ├── img_214.jpg │ ├── img_215.jpg │ ├── img_216.jpg │ ├── img_217.jpg │ ├── img_218.jpg │ ├── img_219.jpg │ ├── img_22.jpg │ ├── img_220.jpg │ ├── img_221.jpg │ ├── img_222.jpg │ ├── img_223.jpg │ ├── img_224.jpg │ ├── img_225.jpg │ ├── img_226.jpg │ ├── img_227.jpg │ ├── img_228.jpg │ ├── img_229.jpg │ ├── img_23.jpg │ ├── img_230.jpg │ ├── img_231.jpg │ ├── img_232.jpg │ ├── img_233.jpg │ ├── img_234.jpg │ ├── img_235.jpg │ ├── img_236.jpg │ ├── img_237.jpg │ ├── img_238.jpg │ ├── img_239.jpg │ ├── img_24.jpg │ ├── img_240.jpg │ ├── img_241.jpg │ ├── img_242.jpg │ ├── img_243.jpg │ ├── img_244.jpg │ ├── img_245.jpg │ ├── img_246.jpg │ ├── img_247.jpg │ ├── img_248.jpg │ ├── img_249.jpg │ ├── img_25.jpg │ ├── img_250.jpg │ ├── img_251.jpg │ ├── img_252.jpg │ ├── img_253.jpg │ ├── img_254.jpg │ ├── img_255.jpg │ ├── img_256.jpg │ ├── img_257.jpg │ ├── img_258.jpg │ ├── img_259.jpg │ ├── img_26.jpg │ ├── img_260.jpg │ ├── img_261.jpg │ ├── img_262.jpg │ ├── img_263.jpg │ ├── img_264.jpg │ ├── img_265.jpg │ ├── img_266.jpg │ ├── img_267.jpg │ ├── img_268.jpg │ ├── img_269.jpg │ ├── img_27.jpg │ ├── img_270.jpg │ ├── img_271.jpg │ ├── img_272.jpg │ ├── img_273.jpg │ ├── img_274.jpg │ ├── img_275.jpg │ ├── img_276.jpg │ ├── img_277.jpg │ ├── img_278.jpg │ ├── img_279.jpg │ ├── img_28.jpg │ ├── img_280.jpg │ ├── img_281.jpg │ ├── img_282.jpg │ ├── img_283.jpg │ ├── img_284.jpg │ ├── img_285.jpg │ ├── img_286.jpg │ ├── img_287.jpg │ ├── img_288.jpg │ ├── img_289.jpg │ ├── img_29.jpg │ ├── img_290.jpg │ ├── img_291.jpg │ ├── img_292.jpg │ ├── img_293.jpg │ ├── img_294.jpg │ ├── img_295.jpg │ ├── img_296.jpg │ ├── img_297.jpg │ ├── img_298.jpg │ ├── img_299.jpg │ ├── img_3.jpg │ ├── img_30.jpg │ ├── img_300.jpg │ ├── img_301.jpg │ ├── img_302.jpg │ ├── img_303.jpg │ ├── img_304.jpg │ ├── img_305.jpg │ ├── img_306.jpg │ ├── img_307.jpg │ ├── img_308.jpg │ ├── img_309.jpg │ ├── img_31.jpg │ ├── img_310.jpg │ ├── img_311.jpg │ ├── img_312.jpg │ ├── img_313.jpg │ ├── img_314.jpg │ ├── img_315.jpg │ ├── img_316.jpg │ ├── img_317.jpg │ ├── img_318.jpg │ ├── img_319.jpg │ ├── img_32.jpg │ ├── img_320.jpg │ ├── img_321.jpg │ ├── img_322.jpg │ ├── img_323.jpg │ ├── img_324.jpg │ ├── img_325.jpg │ ├── img_326.jpg │ ├── img_327.jpg │ ├── img_328.jpg │ ├── img_329.jpg │ ├── img_33.jpg │ ├── img_330.jpg │ ├── img_331.jpg │ ├── img_332.jpg │ ├── img_333.jpg │ ├── img_334.jpg │ ├── img_335.jpg │ ├── img_336.jpg │ ├── img_337.jpg │ ├── img_338.jpg │ ├── img_339.jpg │ ├── img_34.jpg │ ├── img_340.jpg │ ├── img_341.jpg │ ├── img_342.jpg │ ├── img_343.jpg │ ├── img_344.jpg │ ├── img_345.jpg │ ├── img_346.jpg │ ├── img_347.jpg │ ├── img_348.jpg │ ├── img_349.jpg │ ├── img_35.jpg │ ├── img_350.jpg │ ├── img_36.jpg │ ├── img_37.jpg │ ├── img_38.jpg │ ├── img_39.jpg │ ├── img_4.jpg │ ├── img_40.jpg │ ├── img_41.jpg │ ├── img_42.jpg │ ├── img_43.jpg │ ├── img_44.jpg │ ├── img_45.jpg │ ├── img_46.jpg │ ├── img_47.jpg │ ├── img_48.jpg │ ├── img_49.jpg │ ├── img_5.jpg │ ├── img_50.jpg │ ├── img_51.jpg │ ├── img_52.jpg │ ├── img_53.jpg │ ├── img_54.jpg │ ├── img_55.jpg │ ├── img_56.jpg │ ├── img_57.jpg │ ├── img_58.jpg │ ├── img_59.jpg │ ├── img_6.jpg │ ├── img_60.jpg │ ├── img_61.jpg │ ├── img_62.jpg │ ├── img_63.jpg │ ├── img_64.jpg │ ├── img_65.jpg │ ├── img_66.jpg │ ├── img_67.jpg │ ├── img_68.jpg │ ├── img_69.jpg │ ├── img_7.jpg │ ├── img_70.jpg │ ├── img_71.jpg │ ├── img_72.jpg │ ├── img_73.jpg │ ├── img_74.jpg │ ├── img_75.jpg │ ├── img_76.jpg │ ├── img_77.jpg │ ├── img_78.jpg │ ├── img_79.jpg │ ├── img_8.jpg │ ├── img_80.jpg │ ├── img_81.jpg │ ├── img_82.jpg │ ├── img_83.jpg │ ├── img_84.jpg │ ├── img_85.jpg │ ├── img_86.jpg │ ├── img_87.jpg │ ├── img_88.jpg │ ├── img_89.jpg │ ├── img_9.jpg │ ├── img_90.jpg │ ├── img_91.jpg │ ├── img_92.jpg │ ├── img_93.jpg │ ├── img_94.jpg │ ├── img_95.jpg │ ├── img_96.jpg │ ├── img_97.jpg │ ├── img_98.jpg │ └── img_99.jpg ├── test_deepfool.py └── trained │ ├── saved_model.pb │ └── variables │ ├── variables.data-00000-of-00001 │ └── variables.index ├── fgsm ├── FGSM.py └── YellowLabradorLooking_new.jpg └── l2_attack ├── __pycache__ ├── attacker.cpython-35.pyc └── classifier.cpython-35.pyc ├── attacker.py ├── classifier.py ├── l2_attack_onefile.py ├── mnist ├── checkpoint ├── trained_model.data-00000-of-00001 └── trained_model.index ├── models ├── checkpoint ├── mnist.data-00000-of-00001 └── mnist.index └── test.py /README.md: -------------------------------------------------------------------------------- 1 | ### Adversarial Attack 2 | 3 | Implementing adversarial attack using TensorFlow 2.0 4 | 5 | * In deepfool/ folder, deepfool attack is written using TensorFlow 2.0 according to [DeepFool: a simple and accurate method to fool deep neural networks](https://arxiv.org/abs/1511.04599). 6 | 7 | * In l2_attack/ folder, carlini_wagnerL2 attack is written using TensorFlow 2.0 according to [Towards Evaluating the Robustness of Neural Networks](https://arxiv.org/abs/1608.04644). 8 | 9 | * In fgsm/ folder, fast gradient sign method attack is written using TensorFlow 2.0 according to [Explaining and Harnessing Adversarial Examples](https://arxiv.org/abs/1412.6572). -------------------------------------------------------------------------------- /deepfool/__pycache__/deepfool_tf.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/__pycache__/deepfool_tf.cpython-35.pyc -------------------------------------------------------------------------------- /deepfool/deepfool_sim.py: -------------------------------------------------------------------------------- 1 | import copy 2 | import numpy as np 3 | import tensorflow as tf 4 | from PIL import Image 5 | import tensorflow.keras.backend as K 6 | from tensorflow.keras import datasets, optimizers 7 | from tensorflow.keras.models import Sequential 8 | from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, Activation 9 | 10 | 11 | def load_data(): 12 | (train_data, train_labels), (test_data, 13 | test_labels) = datasets.mnist.load_data() 14 | 15 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 16 | train_data = train_data[..., tf.newaxis] 17 | test_data = test_data[..., tf.newaxis] 18 | train_data = tf.cast(train_data, tf.float32) 19 | test_data = tf.cast(test_data, tf.float32) 20 | 21 | train_labels = tf.one_hot(train_labels, 10) 22 | test_labels = tf.one_hot(test_labels, 10) 23 | return train_data, train_labels, test_data, test_labels 24 | 25 | 26 | def loss_func(correct, predicted): 27 | return tf.nn.softmax_cross_entropy_with_logits(labels=correct, logits=predicted) 28 | 29 | 30 | def deepfool(image, model, num_classes=10, overshoot=0.02, max_iter=50, shape=(28, 28, 1)): 31 | image_array = np.array(image) 32 | # print(np.shape(image_array)) # 28*28 33 | 34 | image_norm = tf.cast(image_array / 255.0 - 0.5, tf.float32) 35 | image_norm = np.reshape(image_norm, shape) # 28*28*1 36 | image_norm = image_norm[tf.newaxis, ...] # 1*28*28*1 37 | 38 | print(model(image_norm)) 39 | 40 | f_image = model(image_norm).numpy().flatten() 41 | I = (np.array(f_image)).flatten().argsort()[::-1] 42 | I = I[0:num_classes] 43 | label = I[0] 44 | # print(label, "label") 45 | 46 | input_shape = np.shape(image_norm) 47 | pert_image = copy.deepcopy(image_norm) 48 | w = np.zeros(input_shape) 49 | r_tot = np.zeros(input_shape) 50 | 51 | loop_i = 0 52 | x = tf.Variable(pert_image) 53 | fs = model(x) 54 | k_i = label 55 | 56 | print(fs) # shape=(1, 10) 57 | 58 | def loss_func2(labels, logits, k, I): 59 | # return tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits) 60 | # return tf.reduce_sum(labels * tf.math.log(logits)) 61 | return logits[0, I[k]] 62 | 63 | while k_i == label and loop_i < max_iter: 64 | 65 | pert = np.inf 66 | 67 | one_hot_label_0 = tf.one_hot(label, num_classes) 68 | with tf.GradientTape() as tape: 69 | tape.watch(x) 70 | fs = model(x) 71 | loss_value = loss_func2(one_hot_label_0, fs, 0, I) 72 | print("loss_value", loss_value) 73 | print("fs[0, I[0]]", fs[0, I[0]]) 74 | # grad_orig = tape.gradient(fs[0, I[0]], x) 75 | grad_orig = tape.gradient(loss_value, x) 76 | 77 | for k in range(1, num_classes): 78 | one_hot_label_k = tf.one_hot(I[k], num_classes) 79 | with tf.GradientTape() as tape: 80 | tape.watch(x) 81 | fs = model(x) 82 | loss_value = loss_func2(one_hot_label_k, fs, k, I) 83 | # cur_grad = tape.gradient(fs[0, I[k]], x) 84 | cur_grad = tape.gradient(loss_value, x) 85 | 86 | w_k = cur_grad - grad_orig 87 | 88 | f_k = (fs[0, I[k]] - fs[0, I[0]]).numpy() 89 | 90 | pert_k = abs(f_k) / np.linalg.norm(tf.reshape(w_k, [-1])) 91 | 92 | if pert_k < pert: 93 | pert = pert_k 94 | w = w_k 95 | 96 | # print(pert) # 1.3409956 97 | # print(np.shape(w)) # (1, 28, 28, 1) 98 | r_i = (pert + 1e-4) * w / np.linalg.norm(w) 99 | r_tot = np.float32(r_tot + r_i) 100 | 101 | pert_image = image_norm + (1 + overshoot) * r_tot 102 | 103 | x = tf.Variable(pert_image) 104 | 105 | fs = model(x) 106 | k_i = np.argmax(np.array(fs).flatten()) 107 | 108 | loop_i += 1 109 | 110 | r_tot = (1 + overshoot) * r_tot 111 | 112 | return r_tot, loop_i, label, k_i, pert_image 113 | 114 | 115 | def train_attack(model_file='./trained/', pic_path='testSample/img_2.jpg'): 116 | model = Sequential() 117 | model.add(Conv2D(32, (3, 3))) 118 | model.add(Activation('relu')) 119 | model.add(Conv2D(64, (3, 3))) 120 | model.add(Activation('relu')) 121 | model.add(MaxPooling2D(pool_size=(2, 2))) 122 | model.add(Flatten()) 123 | model.add(Dense(64)) 124 | model.add(Activation('relu')) 125 | model.add(Dense(32)) 126 | model.add(Activation('relu')) 127 | model.add(Dense(10)) 128 | 129 | train_data, train_labels, test_data, test_labels = load_data() 130 | 131 | # model.compile(optimizer=optimizers.Adam(), loss='categorical_crossentropy', metrics=['accuracy']) # loss should be softmax_cross_entropy 132 | model.compile(optimizer=optimizers.Adam(), 133 | loss=loss_func, metrics=['accuracy']) 134 | 135 | # model.fit(train_data, train_labels, epochs=1, batch_size=32) 136 | 137 | # model.evaluate(test_data, test_labels, batch_size=32) 138 | 139 | # tf.saved_model.save(model, model_file) 140 | model = tf.saved_model.load(model_file) 141 | 142 | image = Image.open(pic_path) 143 | 144 | r, loop_i, label_orig, label_pert, pert_image = deepfool(image, model) 145 | print("label_orig: ", label_orig) 146 | print("label_pert: ", label_pert) 147 | 148 | print(model(pert_image)) 149 | # print(pert_image) 150 | pert_image = np.reshape(pert_image, (28, 28)) 151 | 152 | pert_image += 0.5 153 | pert_image *= 255 154 | png = Image.fromarray(pert_image.astype(np.uint8)) 155 | png.save("./hacked.png") 156 | 157 | 158 | train_attack() 159 | -------------------------------------------------------------------------------- /deepfool/deepfool_tf.py: -------------------------------------------------------------------------------- 1 | """ The DeepFool attack """ 2 | 3 | import copy 4 | import numpy as np 5 | import tensorflow as tf 6 | 7 | 8 | def deepfool(image, model, num_classes=10, overshoot=0.02, max_iter=50, shape=(28, 28, 1)): 9 | image_array = np.array(image) 10 | # print(np.shape(image_array)) # 28*28 11 | 12 | image_norm = tf.cast(image_array / 255.0 - 0.5, tf.float32) 13 | image_norm = np.reshape(image_norm, shape) # 28*28*1 14 | image_norm = image_norm[tf.newaxis, ...] # 1*28*28*1 15 | 16 | f_image = model(image_norm).numpy().flatten() 17 | I = (np.array(f_image)).flatten().argsort()[::-1] 18 | I = I[0:num_classes] 19 | label = I[0] 20 | # print(label, "label") 21 | 22 | input_shape = np.shape(image_norm) 23 | pert_image = copy.deepcopy(image_norm) 24 | w = np.zeros(input_shape) 25 | r_tot = np.zeros(input_shape) 26 | 27 | loop_i = 0 28 | x = tf.Variable(pert_image) 29 | fs = model(x) 30 | k_i = label 31 | 32 | print(fs) # shape=(1, 10) 33 | 34 | def loss_func(logits, I, k): 35 | # return tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits) 36 | return logits[0, I[k]] 37 | 38 | while k_i == label and loop_i < max_iter: 39 | 40 | pert = np.inf 41 | 42 | one_hot_label_0 = tf.one_hot(label, num_classes) 43 | with tf.GradientTape() as tape: 44 | tape.watch(x) 45 | fs = model(x) 46 | # loss_value = loss_func(one_hot_label_0, fs) 47 | loss_value = loss_func(fs, I, 0) 48 | # grad_orig = tape.gradient(fs[0, I[0]], x) 49 | grad_orig = tape.gradient(loss_value, x) 50 | 51 | for k in range(1, num_classes): 52 | one_hot_label_k = tf.one_hot(I[k], num_classes) 53 | with tf.GradientTape() as tape: 54 | tape.watch(x) 55 | fs = model(x) 56 | # loss_value = loss_func(one_hot_label_k, fs) 57 | loss_value = loss_func(fs, I, k) 58 | # cur_grad = tape.gradient(fs[0, I[k]], x) 59 | cur_grad = tape.gradient(loss_value, x) 60 | 61 | w_k = cur_grad - grad_orig 62 | 63 | f_k = (fs[0, I[k]] - fs[0, I[0]]).numpy() 64 | 65 | pert_k = abs(f_k) / np.linalg.norm(tf.reshape(w_k, [-1])) 66 | 67 | if pert_k < pert: 68 | pert = pert_k 69 | w = w_k 70 | 71 | # print(pert) # 1.3409956 72 | # print(np.shape(w)) # (1, 28, 28, 1) 73 | r_i = (pert + 1e-4) * w / np.linalg.norm(w) 74 | r_tot = np.float32(r_tot + r_i) 75 | 76 | pert_image = image_norm + (1 + overshoot) * r_tot 77 | 78 | x = tf.Variable(pert_image) 79 | 80 | fs = model(x) 81 | k_i = np.argmax(np.array(fs).flatten()) 82 | 83 | loop_i += 1 84 | 85 | r_tot = (1 + overshoot) * r_tot 86 | 87 | return r_tot, loop_i, label, k_i, pert_image 88 | -------------------------------------------------------------------------------- /deepfool/hacked.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/hacked.png -------------------------------------------------------------------------------- /deepfool/mnist_model.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import tensorflow as tf 3 | 4 | from PIL import Image 5 | from tensorflow.data import Dataset 6 | from tensorflow.keras import Input, Model, optimizers, datasets 7 | from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D 8 | 9 | 10 | class MNISTModel(): 11 | def __init__(self, shape): 12 | inputs = Input(shape=shape) 13 | 14 | x = Conv2D(32, (3, 3), activation='relu')(inputs) 15 | x = Conv2D(64, (3, 3), activation='relu')(x) 16 | x = MaxPooling2D(pool_size=(2, 2))(x) 17 | 18 | x = Flatten()(x) 19 | x = Dense(64, activation='relu')(x) 20 | x = Dense(32, activation='relu')(x) 21 | 22 | outputs = Dense(10)(x) 23 | 24 | self.instance = Model(inputs=inputs, outputs=outputs) 25 | 26 | 27 | def load_data(): 28 | (train_data, train_labels), (test_data, 29 | test_labels) = datasets.mnist.load_data() 30 | 31 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 32 | train_data = train_data[..., tf.newaxis] 33 | test_data = test_data[..., tf.newaxis] 34 | train_data = tf.cast(train_data, tf.float32) 35 | test_data = tf.cast(test_data, tf.float32) 36 | 37 | train_labels = tf.one_hot(train_labels, 10) 38 | test_labels = tf.one_hot(test_labels, 10) 39 | 40 | train_ds = Dataset.from_tensor_slices( 41 | (train_data, train_labels)).shuffle(60000).batch(32) 42 | test_ds = Dataset.from_tensor_slices((test_data, test_labels)).batch(32) 43 | 44 | return train_ds, test_ds 45 | 46 | 47 | def loss_func(correct, predicted): 48 | return tf.nn.softmax_cross_entropy_with_logits(labels=correct, logits=predicted) 49 | 50 | 51 | def train_minst(model_file='./trained/', shape=(28, 28, 1), epochs=5): 52 | train_ds, test_ds = load_data() 53 | model = MNISTModel(shape=shape).instance 54 | model.compile(optimizer=optimizers.Adam(learning_rate=0.003), 55 | loss=loss_func, metrics=['accuracy']) 56 | model.fit(train_ds, epochs=epochs) 57 | tf.saved_model.save(model, model_file) 58 | 59 | results = model.evaluate(test_ds) 60 | print('test loss, test acc:', results) 61 | 62 | 63 | def classifier(pic_path='testSample/img_1.jpg', model_file='./trained/', shape=(28, 28, 1)): 64 | image = Image.open(pic_path) 65 | image_array = np.array(image) 66 | image_norm = tf.cast(image_array / 255.0 - 0.5, tf.float32) 67 | image_norm = np.reshape(image_norm, shape) 68 | image_norm = image_norm[tf.newaxis, ...] 69 | 70 | model = tf.saved_model.load(model_file) 71 | logits = model(image_norm) 72 | 73 | print(logits) 74 | 75 | 76 | train_minst() 77 | classifier() 78 | -------------------------------------------------------------------------------- /deepfool/testSample/img_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_1.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_10.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_10.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_100.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_100.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_101.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_101.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_102.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_102.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_103.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_103.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_104.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_104.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_105.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_105.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_106.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_106.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_107.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_107.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_108.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_108.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_109.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_109.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_11.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_11.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_110.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_110.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_111.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_111.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_112.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_112.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_113.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_113.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_114.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_114.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_115.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_115.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_116.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_116.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_117.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_117.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_118.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_118.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_119.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_119.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_12.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_12.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_120.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_120.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_121.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_121.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_122.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_122.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_123.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_123.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_124.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_124.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_125.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_125.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_126.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_126.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_127.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_127.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_128.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_128.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_129.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_129.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_13.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_13.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_130.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_130.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_131.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_131.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_132.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_132.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_133.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_133.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_134.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_134.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_135.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_135.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_136.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_136.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_137.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_137.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_138.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_138.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_139.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_139.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_14.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_14.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_140.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_140.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_141.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_141.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_142.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_142.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_143.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_143.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_144.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_144.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_145.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_145.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_146.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_146.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_147.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_147.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_148.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_148.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_149.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_149.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_15.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_15.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_150.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_150.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_151.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_151.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_152.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_152.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_153.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_153.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_154.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_154.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_155.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_155.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_156.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_156.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_157.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_157.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_158.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_158.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_159.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_159.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_16.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_16.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_160.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_160.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_161.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_161.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_162.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_162.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_163.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_163.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_164.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_164.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_165.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_165.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_166.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_166.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_167.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_167.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_168.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_168.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_169.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_169.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_17.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_17.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_170.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_170.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_171.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_171.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_172.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_172.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_173.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_173.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_174.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_174.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_175.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_175.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_176.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_176.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_177.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_177.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_178.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_178.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_179.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_179.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_18.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_18.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_180.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_180.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_181.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_181.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_182.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_182.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_183.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_183.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_184.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_184.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_185.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_185.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_186.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_186.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_187.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_187.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_188.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_188.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_189.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_189.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_19.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_19.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_190.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_190.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_191.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_191.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_192.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_192.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_193.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_193.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_194.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_194.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_195.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_195.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_196.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_196.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_197.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_197.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_198.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_198.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_199.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_199.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_2.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_20.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_20.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_200.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_200.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_201.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_201.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_202.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_202.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_203.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_203.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_204.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_204.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_205.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_205.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_206.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_206.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_207.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_207.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_208.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_208.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_209.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_209.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_21.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_21.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_210.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_210.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_211.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_211.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_212.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_212.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_213.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_213.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_214.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_214.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_215.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_215.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_216.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_216.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_217.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_217.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_218.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_218.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_219.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_219.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_22.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_22.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_220.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_220.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_221.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_221.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_222.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_222.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_223.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_223.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_224.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_224.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_225.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_225.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_226.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_226.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_227.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_227.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_228.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_228.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_229.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_229.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_23.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_23.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_230.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_230.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_231.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_231.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_232.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_232.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_233.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_233.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_234.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_234.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_235.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_235.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_236.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_236.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_237.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_237.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_238.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_238.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_239.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_239.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_24.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_24.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_240.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_240.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_241.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_241.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_242.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_242.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_243.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_243.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_244.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_244.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_245.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_245.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_246.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_246.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_247.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_247.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_248.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_248.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_249.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_249.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_25.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_25.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_250.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_250.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_251.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_251.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_252.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_252.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_253.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_253.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_254.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_254.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_255.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_255.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_256.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_256.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_257.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_257.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_258.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_258.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_259.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_259.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_26.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_26.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_260.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_260.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_261.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_261.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_262.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_262.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_263.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_263.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_264.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_264.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_265.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_265.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_266.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_266.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_267.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_267.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_268.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_268.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_269.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_269.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_27.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_27.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_270.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_270.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_271.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_271.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_272.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_272.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_273.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_273.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_274.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_274.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_275.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_275.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_276.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_276.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_277.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_277.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_278.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_278.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_279.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_279.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_28.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_28.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_280.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_280.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_281.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_281.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_282.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_282.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_283.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_283.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_284.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_284.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_285.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_285.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_286.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_286.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_287.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_287.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_288.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_288.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_289.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_289.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_29.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_29.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_290.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_290.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_291.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_291.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_292.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_292.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_293.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_293.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_294.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_294.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_295.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_295.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_296.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_296.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_297.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_297.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_298.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_298.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_299.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_299.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_3.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_30.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_30.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_300.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_300.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_301.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_301.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_302.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_302.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_303.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_303.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_304.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_304.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_305.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_305.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_306.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_306.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_307.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_307.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_308.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_308.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_309.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_309.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_31.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_31.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_310.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_310.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_311.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_311.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_312.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_312.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_313.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_313.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_314.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_314.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_315.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_315.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_316.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_316.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_317.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_317.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_318.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_318.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_319.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_319.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_32.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_32.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_320.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_320.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_321.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_321.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_322.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_322.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_323.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_323.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_324.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_324.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_325.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_325.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_326.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_326.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_327.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_327.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_328.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_328.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_329.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_329.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_33.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_33.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_330.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_330.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_331.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_331.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_332.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_332.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_333.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_333.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_334.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_334.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_335.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_335.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_336.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_336.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_337.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_337.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_338.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_338.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_339.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_339.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_34.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_34.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_340.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_340.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_341.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_341.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_342.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_342.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_343.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_343.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_344.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_344.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_345.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_345.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_346.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_346.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_347.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_347.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_348.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_348.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_349.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_349.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_35.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_35.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_350.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_350.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_36.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_36.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_37.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_37.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_38.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_38.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_39.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_39.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_4.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_40.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_40.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_41.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_41.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_42.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_42.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_43.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_43.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_44.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_44.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_45.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_45.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_46.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_46.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_47.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_47.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_48.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_48.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_49.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_49.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_5.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_50.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_50.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_51.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_51.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_52.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_52.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_53.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_53.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_54.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_54.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_55.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_55.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_56.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_56.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_57.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_57.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_58.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_58.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_59.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_59.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_6.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_6.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_60.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_60.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_61.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_61.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_62.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_62.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_63.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_63.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_64.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_64.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_65.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_65.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_66.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_66.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_67.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_67.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_68.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_68.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_69.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_69.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_7.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_7.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_70.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_70.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_71.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_71.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_72.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_72.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_73.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_73.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_74.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_74.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_75.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_75.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_76.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_76.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_77.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_77.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_78.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_78.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_79.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_79.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_8.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_8.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_80.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_80.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_81.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_81.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_82.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_82.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_83.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_83.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_84.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_84.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_85.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_85.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_86.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_86.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_87.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_87.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_88.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_88.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_89.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_89.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_9.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_9.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_90.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_90.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_91.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_91.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_92.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_92.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_93.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_93.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_94.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_94.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_95.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_95.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_96.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_96.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_97.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_97.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_98.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_98.jpg -------------------------------------------------------------------------------- /deepfool/testSample/img_99.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/testSample/img_99.jpg -------------------------------------------------------------------------------- /deepfool/test_deepfool.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import tensorflow as tf 3 | from PIL import Image 4 | from deepfool_tf import deepfool 5 | 6 | 7 | def test_deepfool(model_file='./trained/', pic_path='testSample/img_12.jpg'): 8 | image = Image.open(pic_path) 9 | model = tf.saved_model.load(model_file) 10 | 11 | r, loop_i, label_orig, label_pert, pert_image = deepfool(image, model) 12 | print("label_orig: ", label_orig) 13 | print("label_pert: ", label_pert) 14 | 15 | pert_image = np.reshape(pert_image, (28, 28)) 16 | 17 | pert_image += 0.5 18 | pert_image *= 255 19 | png = Image.fromarray(pert_image.astype(np.uint8)) 20 | png.save("./hacked.png") 21 | 22 | 23 | test_deepfool() 24 | -------------------------------------------------------------------------------- /deepfool/trained/saved_model.pb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/trained/saved_model.pb -------------------------------------------------------------------------------- /deepfool/trained/variables/variables.data-00000-of-00001: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/trained/variables/variables.data-00000-of-00001 -------------------------------------------------------------------------------- /deepfool/trained/variables/variables.index: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/deepfool/trained/variables/variables.index -------------------------------------------------------------------------------- /fgsm/FGSM.py: -------------------------------------------------------------------------------- 1 | from __future__ import absolute_import, division, print_function, unicode_literals 2 | 3 | import numpy as np 4 | import tensorflow as tf 5 | import matplotlib as mpl 6 | import matplotlib.pyplot as plt 7 | from tensorflow.keras.preprocessing import image 8 | from tensorflow.keras.applications.inception_v3 import InceptionV3, preprocess_input, decode_predictions 9 | 10 | 11 | def prepare(img_path='./YellowLabradorLooking_new.jpg'): 12 | img = image.load_img(img_path, target_size=(299, 299)) 13 | img = image.img_to_array(img) 14 | img = preprocess_input(img) 15 | img = img[tf.newaxis, ...] 16 | img = tf.Variable(img, dtype=tf.float32) 17 | 18 | model = InceptionV3(include_top=True, weights="imagenet") 19 | model.trainable = False 20 | return img, model 21 | 22 | 23 | def loss_object(label, predict): 24 | return tf.keras.losses.categorical_crossentropy(label, predict) 25 | 26 | 27 | def train_step(model, img, label): 28 | with tf.GradientTape() as tape: 29 | tape.watch(img) 30 | predict = model(img) 31 | # target attack, so minimize the loss 32 | loss = -loss_object(label, predict) 33 | grad = tape.gradient(loss, img) 34 | signed_grad = tf.sign(grad) 35 | # optimizer = tf.keras.optimizers.Adam() 36 | # optimizer.apply_gradients(zip(signed_grad, [img])) # the shape of img is auot reduced from (1,299, 299, 3) to (299, 299, 3) 37 | # return img 38 | return signed_grad 39 | 40 | 41 | def target_attack(img_path='./YellowLabradorLooking_new.jpg', label=100, target=True, steps=100, step_alpha=1e-4): 42 | img, model = prepare(img_path) 43 | label = tf.one_hot(label, 1000) 44 | 45 | for i in range(steps): 46 | signed_grad = train_step(model, img, label) 47 | normed_grad = step_alpha * signed_grad 48 | img = img + normed_grad 49 | # img = train_step(model, img, label) 50 | if np.argmax(label) == np.argmax(model(img)): 51 | break 52 | result = model.predict(img) 53 | print(decode_predictions(result, top=1), i) 54 | return img 55 | 56 | 57 | pert = target_attack() 58 | pert = tf.clip_by_value(pert, 0, 1) 59 | plt.imshow(pert[0]) 60 | plt.show() 61 | -------------------------------------------------------------------------------- /fgsm/YellowLabradorLooking_new.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/fgsm/YellowLabradorLooking_new.jpg -------------------------------------------------------------------------------- /l2_attack/__pycache__/attacker.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/__pycache__/attacker.cpython-35.pyc -------------------------------------------------------------------------------- /l2_attack/__pycache__/classifier.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/__pycache__/classifier.cpython-35.pyc -------------------------------------------------------------------------------- /l2_attack/attacker.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import numpy as np 3 | import tensorflow as tf 4 | from tensorflow.keras import optimizers 5 | 6 | BINARY_SEARCH_STEPS = 9 # number of times to adjust the constant with binary search 7 | MAX_ITERATIONS = 1000 # number of iterations to perform gradient descent 8 | ABORT_EARLY = True # if we stop improving, abort gradient descent early 9 | LEARNING_RATE = 1e-2 # larger values converge faster to less accurate results 10 | TARGETED = True # should we target one specific class? or just be wrong? 11 | CONFIDENCE = 0 # how strong the adversarial example should be 12 | INITIAL_CONST = 1e-3 # the initial constant c to pick as a first guess 13 | 14 | 15 | class CarliniL2: 16 | def __init__(self, model, batch_size=1, confidence=CONFIDENCE, targeted=TARGETED, learning_rate=LEARNING_RATE, binary_search_steps=BINARY_SEARCH_STEPS, max_iterations=MAX_ITERATIONS, abort_early=ABORT_EARLY, initial_const=INITIAL_CONST, boxmin=-0.5, boxmax=0.5): 17 | # image_size, num_channels, num_labels = model.image_size, model.num_channels, model.num_labels 18 | image_size, num_channels, num_labels = 28, 1, 10 19 | self.TARGETED = targeted 20 | self.LEARNING_RATE = learning_rate 21 | self.MAX_ITERATIONS = max_iterations 22 | self.BINARY_SEARCH_STEPS = binary_search_steps 23 | self.ABORT_EARLY = abort_early 24 | self.CONFIDENCE = confidence 25 | self.initial_const = initial_const 26 | self.batch_size = batch_size 27 | 28 | self.repeat = binary_search_steps >= 10 29 | 30 | self.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK = False 31 | 32 | self.shape = (batch_size, image_size, image_size, num_channels) 33 | self.boxmul = (boxmax - boxmin) / 2. 34 | self.boxplus = (boxmin + boxmax) / 2. 35 | self.model = model 36 | 37 | def attack(self, imgs, targets): 38 | """ 39 | Perform the L_2 attack on the given images for the given targets. 40 | 41 | If self.targeted is true, then the targets represents the target labels. 42 | If self.targeted is false, then targets are the original class labels. 43 | """ 44 | r = [] 45 | print('go up to', len(imgs)) 46 | for i in range(0, len(imgs), self.batch_size): 47 | print('tick', i) 48 | # print("imgs[i:i + self.batch_size]", imgs[i:i + self.batch_size]) 49 | # print("targets", targets) 50 | r.extend(self.attack_batch( 51 | imgs[i:i + self.batch_size], targets)) 52 | return np.array(r) 53 | 54 | def attack_batch(self, imgs, labs): 55 | """ 56 | Run the attack on a batch of images and labels. 57 | """ 58 | # print("imgs, labs in attack_batch", imgs, labs) #shape=(1, 28, 28, 1), dtype=float32) [array([0., 0., 0., 0., 0., 0., 1., 0., 0., 0.])] 59 | 60 | batch_size = self.batch_size 61 | 62 | def compare(x, y): 63 | 64 | if not isinstance(x, (float, int, np.int64)): 65 | x = x.numpy() 66 | x = np.copy(x) 67 | if self.TARGETED: 68 | x[y] -= self.CONFIDENCE 69 | else: 70 | x[y] += self.CONFIDENCE 71 | x = np.argmax(x) 72 | if self.TARGETED: 73 | return x == y 74 | else: 75 | return x != y 76 | 77 | # @tf.function 78 | def train_step(modifier, timg, tlab, const): 79 | with tf.GradientTape() as tape: 80 | newimg = tf.tanh(modifier + timg) * self.boxmul + self.boxplus 81 | # newimg = np.random.rand(1, 28, 28, 1) 82 | output = self.model(newimg) 83 | output = tf.cast(output, dtype=tf.float32) 84 | l2dist = tf.reduce_sum( 85 | tf.square(newimg - (tf.tanh(timg) * self.boxmul + self.boxplus)), [1, 2, 3]) 86 | real = tf.math.reduce_sum((tlab) * output, 1) 87 | other = tf.math.reduce_max( 88 | (1 - tlab) * output - (tlab * 10000), 1) 89 | if self.TARGETED: 90 | # if targetted, optimize for making the other class most likely 91 | loss1 = tf.maximum(0.0, other - real + self.CONFIDENCE) 92 | else: 93 | # if untargeted, optimize for making this class least likely. 94 | loss1 = tf.maximum(0.0, real - other + self.CONFIDENCE) 95 | 96 | loss2 = tf.reduce_sum(l2dist) 97 | loss1 = tf.reduce_sum(const * loss1) 98 | 99 | loss = loss1 + loss2 100 | optimizer = optimizers.Adam(self.LEARNING_RATE) 101 | loss_metric = tf.keras.metrics.Mean(name='train_loss') 102 | 103 | grads = tape.gradient(loss, [modifier]) 104 | optimizer.apply_gradients(zip(grads, [modifier])) 105 | loss_metric.update_state(loss) 106 | return loss, l2dist, output, newimg, loss1, loss2 107 | 108 | # convert to tanh-space 109 | imgs = np.arctanh((imgs - self.boxplus) / self.boxmul * 0.999999) 110 | # print(np.shape(imgs)) 111 | lower_bound = np.zeros(batch_size) 112 | CONST = np.ones(batch_size) * self.initial_const 113 | upper_bound = np.ones(batch_size) * 1e10 114 | 115 | # the best l2, score, and image attack 116 | o_bestl2 = [1e10] * batch_size 117 | o_bestscore = [-1] * batch_size 118 | o_bestattack = [np.zeros(imgs[0].shape)] * batch_size 119 | print(np.shape(o_bestattack), "np.shape(o_bestattack)") # (1, 28, 28, 1) 120 | 121 | for outer_step in range(self.BINARY_SEARCH_STEPS): 122 | batch = tf.Variable(imgs[:batch_size], dtype=tf.float32) 123 | batchlab = tf.Variable(labs[:batch_size], dtype=tf.float32) 124 | # print("*******batchlab***********", batchlab) # shape=(1, 10) 125 | bestl2 = [1e10] * batch_size 126 | bestscore = [-1] * batch_size 127 | if self.repeat == True and outer_step == self.BINARY_SEARCH_STEPS - 1: 128 | CONST = upper_bound 129 | 130 | modifier = tf.Variable(np.zeros((1, 28, 28, 1), dtype=np.float32)) 131 | const = tf.Variable(CONST, dtype=tf.float32) 132 | prev = np.inf 133 | for iteration in range(self.MAX_ITERATIONS): 134 | # perform the attack 135 | 136 | l, l2s, scores, nimg, loss1, loss2 = train_step( 137 | modifier, batch, batchlab, const) 138 | 139 | if np.all(scores >= -.0001) and np.all(scores <= 1.0001): 140 | if np.allclose(np.sum(scores, axis=1), 1.0, atol=1e-3): 141 | if not self.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK: 142 | raise Exception("The output of model.predict should return the pre-softmax layer. It looks like you are returning the probability vector (post-softmax). If you are sure you want to do that, set attack.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK = True") 143 | 144 | if iteration % (self.MAX_ITERATIONS // 10) == 0: 145 | print(iteration, l, loss1, loss2) 146 | # check if we should abort search if we're getting nowhere. 147 | if self.ABORT_EARLY and iteration % (self.MAX_ITERATIONS // 10) == 0: 148 | if l > prev * .9999: 149 | break 150 | prev = l 151 | # adjust the best result found so far 152 | for e, (l2, sc, ii) in enumerate(zip(l2s, scores, nimg)): 153 | # print("batchlab", np.argmax(batchlab[e])) 154 | # print("(sc, np.argmax(batchlab))", sc, np.argmax(sc)) 155 | # print("l2 and bestl2[e]", l2, bestl2[e]) 156 | # print("compare(sc, tf.argmax(batchlab))", 157 | # compare(sc, tf.argmax(batchlab[e]))) 158 | if l2 < bestl2[e] and compare(sc, np.argmax(batchlab[e])): 159 | bestl2[e] = l2 160 | bestscore[e] = np.argmax(sc) 161 | if l2 < o_bestl2[e] and compare(sc, np.argmax(batchlab[e])): 162 | o_bestl2[e] = l2 163 | o_bestscore[e] = np.argmax(sc) 164 | o_bestattack[e] = ii 165 | 166 | # adjust the constant as needed 167 | for e in range(batch_size): 168 | print("bestscore[e]", bestscore[e]) 169 | if compare(bestscore[e], np.argmax(batchlab[e])) and bestscore[e] != -1: 170 | # success, divide const by two 171 | upper_bound[e] = min(upper_bound[e], CONST[e]) 172 | if upper_bound[e] < 1e9: 173 | CONST[e] = (lower_bound[e] + upper_bound[e]) / 2 174 | else: 175 | # failure, either multiply by 10 if no solution found yet 176 | # or do binary search with the known upper bound 177 | lower_bound[e] = max(lower_bound[e], CONST[e]) 178 | if upper_bound[e] < 1e9: 179 | CONST[e] = (lower_bound[e] + upper_bound[e]) / 2 180 | else: 181 | CONST[e] *= 10 182 | o_bestl2 = np.array(o_bestl2) 183 | return o_bestattack 184 | -------------------------------------------------------------------------------- /l2_attack/classifier.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import tensorflow as tf 3 | from tensorflow.data import Dataset 4 | from tensorflow.keras import datasets, Model, losses, optimizers, metrics 5 | from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, BatchNormalization 6 | 7 | 8 | class MNISTModel(Model): 9 | def __init__(self): 10 | super(MNISTModel, self).__init__() 11 | self.conv1 = Conv2D(32, (3, 3), activation='relu', 12 | input_shape=(28, 28, 1)) 13 | self.conv2 = Conv2D(32, (3, 3), activation='relu') 14 | self.conv3 = Conv2D(64, (3, 3), activation='relu') 15 | self.conv4 = Conv2D(128, (3, 3), activation='relu') 16 | self.maxpo = MaxPooling2D(pool_size=(2, 2)) 17 | self.batch = BatchNormalization() 18 | self.flatt = Flatten() 19 | self.dense = Dense(64, activation='relu') 20 | self.dens1 = Dense(32, activation='relu') 21 | self.dens2 = Dense(10) 22 | 23 | def call(self, x): 24 | x = self.conv1(x) 25 | x = self.conv2(x) 26 | x = self.batch(x) 27 | x = self.conv3(x) 28 | x = self.maxpo(x) 29 | x = self.conv4(x) 30 | x = self.maxpo(x) 31 | x = self.flatt(x) 32 | x = self.dense(x) 33 | x = self.dens1(x) 34 | return self.dens2(x) 35 | 36 | 37 | def load_data(): 38 | (train_data, train_labels), (test_data, 39 | test_labels) = datasets.mnist.load_data() 40 | 41 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 42 | train_data = train_data[..., tf.newaxis] 43 | test_data = test_data[..., tf.newaxis] 44 | train_data = tf.cast(train_data, tf.float32) 45 | test_data = tf.cast(test_data, tf.float32) 46 | 47 | train_labels = tf.one_hot(train_labels, 10) 48 | test_labels = tf.one_hot(test_labels, 10) 49 | 50 | train_ds = Dataset.from_tensor_slices( 51 | (train_data, train_labels)).shuffle(60000).batch(32) 52 | test_ds = Dataset.from_tensor_slices((test_data, test_labels)).batch(32) 53 | 54 | return train_ds, test_ds 55 | 56 | 57 | def train(model_file='./mnist/trained_model', num_epochs=5, init=None): 58 | 59 | train_ds, test_ds = load_data() 60 | 61 | model = MNISTModel() 62 | 63 | optimizer = optimizers.Adam() 64 | 65 | train_loss = metrics.Mean(name='train_loss') 66 | train_accuracy = metrics.CategoricalAccuracy(name='train_accuracy') 67 | 68 | test_loss = metrics.Mean(name='test_loss') 69 | test_accuracy = metrics.CategoricalAccuracy(name='test_accuracy') 70 | 71 | if init != None: 72 | model.load_weights(model_file) 73 | 74 | @tf.function 75 | def train_step(images, labels): 76 | with tf.GradientTape() as tape: 77 | logits = model(images) 78 | loss_value = loss_object(labels, logits) 79 | grads = tape.gradient(loss_value, model.trainable_variables) 80 | optimizer.apply_gradients(zip(grads, model.trainable_variables)) 81 | train_loss(loss_value) 82 | train_accuracy(labels, logits) 83 | 84 | @tf.function 85 | def test_step(images, labels): 86 | logits = model(images) 87 | loss_value = loss_object(labels, logits) 88 | test_loss(loss_value) 89 | test_accuracy(labels, logits) 90 | 91 | def loss_object(labels, logits): 92 | return tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits) 93 | 94 | for epoch in range(num_epochs): 95 | for images, labels in train_ds: 96 | train_step(images, labels) 97 | 98 | for test_images, test_labels in test_ds: 99 | test_step(test_images, test_labels) 100 | 101 | template = 'Epoch {}, Loss: {}, Accuracy: {}, Test Loss: {}, Test Accuracy: {}' 102 | print (template.format(epoch + 1, train_loss.result(), train_accuracy.result() 103 | * 100, test_loss.result(), test_accuracy.result() * 100)) 104 | 105 | model.save_weights(model_file) 106 | 107 | 108 | # train() 109 | -------------------------------------------------------------------------------- /l2_attack/l2_attack_onefile.py: -------------------------------------------------------------------------------- 1 | import time 2 | import numpy as np 3 | import tensorflow as tf 4 | from tensorflow.keras.models import Sequential 5 | from tensorflow.keras import datasets, optimizers 6 | from tensorflow.keras.layers import Dense, Flatten, Conv2D, Activation, MaxPooling2D, Dropout 7 | 8 | 9 | class MNISTModel: 10 | def __init__(self, restore): 11 | self.num_channels = 1 12 | self.image_size = 28 13 | self.num_labels = 10 14 | 15 | model = Sequential() 16 | 17 | model.add(Conv2D(32, (3, 3), 18 | input_shape=(28, 28, 1))) 19 | model.add(Activation('relu')) 20 | model.add(Conv2D(32, (3, 3))) 21 | model.add(Activation('relu')) 22 | model.add(MaxPooling2D(pool_size=(2, 2))) 23 | 24 | model.add(Conv2D(64, (3, 3))) 25 | model.add(Activation('relu')) 26 | model.add(Conv2D(64, (3, 3))) 27 | model.add(Activation('relu')) 28 | model.add(MaxPooling2D(pool_size=(2, 2))) 29 | 30 | model.add(Flatten()) 31 | model.add(Dense(200)) 32 | model.add(Activation('relu')) 33 | model.add(Dense(200)) 34 | model.add(Activation('relu')) 35 | model.add(Dense(10)) 36 | model.load_weights(restore) 37 | 38 | self.model = model 39 | 40 | def predict(self, data): 41 | return self.model(data) 42 | 43 | 44 | def load_data(): 45 | (train_data, train_labels), (test_data, 46 | test_labels) = datasets.mnist.load_data() 47 | 48 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 49 | train_data = train_data[..., tf.newaxis] 50 | test_data = test_data[..., tf.newaxis] 51 | train_data = tf.cast(train_data, tf.float32) 52 | test_data = tf.cast(test_data, tf.float32) 53 | 54 | train_labels = tf.one_hot(train_labels, 10) 55 | test_labels = tf.one_hot(test_labels, 10) 56 | return (train_data, train_labels, test_data, test_labels) 57 | 58 | 59 | def train(data, file_name, params, num_epochs=50, batch_size=128, train_temp=1, init=None): 60 | """ 61 | Standard neural network training procedure. 62 | """ 63 | model = Sequential() 64 | 65 | model.add(Conv2D(params[0], (3, 3), 66 | input_shape=data[0].shape[1:])) 67 | model.add(Activation('relu')) 68 | model.add(Conv2D(params[1], (3, 3))) 69 | model.add(Activation('relu')) 70 | model.add(MaxPooling2D(pool_size=(2, 2))) 71 | 72 | model.add(Conv2D(params[2], (3, 3))) 73 | model.add(Activation('relu')) 74 | model.add(Conv2D(params[3], (3, 3))) 75 | model.add(Activation('relu')) 76 | model.add(MaxPooling2D(pool_size=(2, 2))) 77 | 78 | model.add(Flatten()) 79 | model.add(Dense(params[4])) 80 | model.add(Activation('relu')) 81 | model.add(Dropout(0.5)) 82 | model.add(Dense(params[5])) 83 | model.add(Activation('relu')) 84 | model.add(Dense(10)) 85 | 86 | if init != None: 87 | model.load_weights(init) 88 | 89 | def fn(correct, predicted): 90 | return tf.nn.softmax_cross_entropy_with_logits(labels=correct, 91 | logits=predicted / train_temp) 92 | 93 | sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) 94 | 95 | model.compile(loss=fn, 96 | optimizer=sgd, 97 | metrics=['accuracy']) 98 | 99 | model.fit(data[0], data[1], batch_size=batch_size, 100 | nb_epoch=num_epochs, shuffle=True) 101 | 102 | if file_name != None: 103 | model.save_weights(file_name) 104 | 105 | return model 106 | 107 | 108 | def show(img): 109 | """ 110 | Show MNSIT digits in the console. 111 | """ 112 | # if not isinstance(img, list): 113 | # img = img.numpy() 114 | # else: 115 | # img = np.array(img) 116 | img = np.array(img) 117 | remap = " .*#" + "#" * 100 118 | img = (img.flatten() + .5) * 3 119 | if len(img) != 784: 120 | return 121 | print("START") 122 | for i in range(28): 123 | print("".join([remap[int(round(x))] for x in img[i * 28:i * 28 + 28]])) 124 | 125 | 126 | BINARY_SEARCH_STEPS = 9 # number of times to adjust the constant with binary search 127 | MAX_ITERATIONS = 1000 # number of iterations to perform gradient descent 128 | ABORT_EARLY = True # if we stop improving, abort gradient descent early 129 | LEARNING_RATE = 1e-2 # larger values converge faster to less accurate results 130 | TARGETED = True # should we target one specific class? or just be wrong? 131 | CONFIDENCE = 0 # how strong the adversarial example should be 132 | INITIAL_CONST = 1e-3 # the initial constant c to pick as a first guess 133 | 134 | 135 | class CarliniL2: 136 | def __init__(self, model, batch_size=1, confidence=CONFIDENCE, targeted=TARGETED, learning_rate=LEARNING_RATE, binary_search_steps=BINARY_SEARCH_STEPS, max_iterations=MAX_ITERATIONS, abort_early=ABORT_EARLY, initial_const=INITIAL_CONST, boxmin=-0.5, boxmax=0.5): 137 | image_size, num_channels, num_labels = model.image_size, model.num_channels, model.num_labels 138 | self.TARGETED = targeted 139 | self.LEARNING_RATE = learning_rate 140 | self.MAX_ITERATIONS = max_iterations 141 | self.BINARY_SEARCH_STEPS = binary_search_steps 142 | self.ABORT_EARLY = abort_early 143 | self.CONFIDENCE = confidence 144 | self.initial_const = initial_const 145 | self.batch_size = batch_size 146 | 147 | self.repeat = binary_search_steps >= 10 148 | 149 | self.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK = False 150 | 151 | self.shape = (batch_size, image_size, image_size, num_channels) 152 | self.boxmul = (boxmax - boxmin) / 2. 153 | self.boxplus = (boxmin + boxmax) / 2. 154 | 155 | def attack(self, imgs, targets): 156 | """ 157 | Perform the L_2 attack on the given images for the given targets. 158 | 159 | If self.targeted is true, then the targets represents the target labels. 160 | If self.targeted is false, then targets are the original class labels. 161 | """ 162 | r = [] 163 | print('go up to', len(imgs)) 164 | for i in range(0, len(imgs), self.batch_size): 165 | print('tick', i) 166 | r.extend(self.attack_batch( 167 | imgs[i:i + self.batch_size], targets)) 168 | return np.array(r) 169 | 170 | def attack_batch(self, imgs, labs): 171 | """ 172 | Run the attack on a batch of images and labels. 173 | """ 174 | # print("imgs, labs in attack_batch", imgs, labs) #shape=(1, 28, 28, 1), dtype=float32) [array([0., 0., 0., 0., 0., 0., 1., 0., 0., 0.])] 175 | 176 | batch_size = self.batch_size 177 | 178 | def compare(x, y): 179 | if not isinstance(x, (float, int, np.int64)): 180 | x = x.numpy() 181 | x = np.copy(x) 182 | if self.TARGETED: 183 | x[y] -= self.CONFIDENCE 184 | else: 185 | x[y] += self.CONFIDENCE 186 | x = np.argmax(x) 187 | if self.TARGETED: 188 | return x == y 189 | else: 190 | return x != y 191 | 192 | # @tf.function 193 | def train_step(modifier, timg, tlab, const): 194 | with tf.GradientTape() as tape: 195 | newimg = tf.tanh(modifier + timg) * self.boxmul + self.boxplus 196 | # newimg = np.random.rand(1, 28, 28, 1) 197 | output = model.predict(newimg) 198 | output = tf.cast(output, dtype=tf.float32) 199 | l2dist = tf.reduce_sum( 200 | tf.square(newimg - (tf.tanh(timg) * self.boxmul + self.boxplus)), [1, 2, 3]) 201 | real = tf.math.reduce_sum((tlab) * output, 1) 202 | other = tf.math.reduce_max( 203 | (1 - tlab) * output - (tlab * 10000), 1) 204 | if self.TARGETED: 205 | # if targetted, optimize for making the other class most likely 206 | loss1 = tf.maximum(0.0, other - real + self.CONFIDENCE) 207 | else: 208 | # if untargeted, optimize for making this class least likely. 209 | loss1 = tf.maximum(0.0, real - other + self.CONFIDENCE) 210 | 211 | loss2 = tf.reduce_sum(l2dist) 212 | loss1 = tf.reduce_sum(const * loss1) 213 | 214 | loss = loss1 + loss2 215 | optimizer = optimizers.Adam(self.LEARNING_RATE) 216 | loss_metric = tf.keras.metrics.Mean(name='train_loss') 217 | # optimizer.minimize(self.loss, var_list=[modifier]) 218 | grads = tape.gradient(loss, [modifier]) 219 | optimizer.apply_gradients(zip(grads, [modifier])) 220 | loss_metric.update_state(loss) 221 | return loss, l2dist, output, newimg, loss1, loss2 222 | 223 | # convert to tanh-space 224 | imgs = np.arctanh((imgs - self.boxplus) / self.boxmul * 0.999999) 225 | # print(np.shape(imgs)) 226 | lower_bound = np.zeros(batch_size) 227 | CONST = np.ones(batch_size) * self.initial_const 228 | upper_bound = np.ones(batch_size) * 1e10 229 | 230 | # the best l2, score, and image attack 231 | o_bestl2 = [1e10] * batch_size 232 | o_bestscore = [-1] * batch_size 233 | o_bestattack = [np.zeros(imgs[0].shape)] * batch_size 234 | print(np.shape(o_bestattack), "np.shape(o_bestattack)") # (1, 28, 28, 1) 235 | 236 | for outer_step in range(self.BINARY_SEARCH_STEPS): 237 | batch = tf.Variable(imgs[:batch_size], dtype=tf.float32) 238 | batchlab = tf.Variable(labs[:batch_size], dtype=tf.float32) 239 | # print("*******batchlab***********", batchlab) # shape=(1, 10) 240 | bestl2 = [1e10] * batch_size 241 | bestscore = [-1] * batch_size 242 | if self.repeat == True and outer_step == self.BINARY_SEARCH_STEPS - 1: 243 | CONST = upper_bound 244 | 245 | modifier = tf.Variable(np.zeros((1, 28, 28, 1), dtype=np.float32)) 246 | const = tf.Variable(CONST, dtype=tf.float32) 247 | prev = np.inf 248 | for iteration in range(self.MAX_ITERATIONS): 249 | # perform the attack 250 | 251 | l, l2s, scores, nimg, loss1, loss2 = train_step( 252 | modifier, batch, batchlab, const) 253 | if np.all(scores >= -.0001) and np.all(scores <= 1.0001): 254 | if np.allclose(np.sum(scores, axis=1), 1.0, atol=1e-3): 255 | if not self.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK: 256 | raise Exception("The output of model.predict should return the pre-softmax layer. It looks like you are returning the probability vector (post-softmax). If you are sure you want to do that, set attack.I_KNOW_WHAT_I_AM_DOING_AND_WANT_TO_OVERRIDE_THE_PRESOFTMAX_CHECK = True") 257 | 258 | if iteration % (self.MAX_ITERATIONS // 10) == 0: 259 | print(iteration, l, loss1, loss2) 260 | # check if we should abort search if we're getting nowhere. 261 | if self.ABORT_EARLY and iteration % (self.MAX_ITERATIONS // 10) == 0: 262 | if l > prev * .9999: 263 | break 264 | prev = l 265 | # adjust the best result found so far 266 | for e, (l2, sc, ii) in enumerate(zip(l2s, scores, nimg)): 267 | # print("batchlab", np.argmax(batchlab[e])) 268 | # print("(sc, np.argmax(batchlab))", sc, np.argmax(sc)) 269 | # print("l2 and bestl2[e]", l2, bestl2[e]) 270 | # print("compare(sc, tf.argmax(batchlab))", 271 | # compare(sc, tf.argmax(batchlab[e]))) 272 | if l2 < bestl2[e] and compare(sc, np.argmax(batchlab[e])): 273 | bestl2[e] = l2 274 | bestscore[e] = np.argmax(sc) 275 | if l2 < o_bestl2[e] and compare(sc, np.argmax(batchlab[e])): 276 | o_bestl2[e] = l2 277 | o_bestscore[e] = np.argmax(sc) 278 | o_bestattack[e] = ii 279 | 280 | # adjust the constant as needed 281 | for e in range(batch_size): 282 | print("bestscore[e]", bestscore[e]) 283 | if compare(bestscore[e], np.argmax(batchlab[e])) and bestscore[e] != -1: 284 | # success, divide const by two 285 | upper_bound[e] = min(upper_bound[e], CONST[e]) 286 | if upper_bound[e] < 1e9: 287 | CONST[e] = (lower_bound[e] + upper_bound[e]) / 2 288 | else: 289 | # failure, either multiply by 10 if no solution found yet 290 | # or do binary search with the known upper bound 291 | lower_bound[e] = max(lower_bound[e], CONST[e]) 292 | if upper_bound[e] < 1e9: 293 | CONST[e] = (lower_bound[e] + upper_bound[e]) / 2 294 | else: 295 | CONST[e] *= 10 296 | o_bestl2 = np.array(o_bestl2) 297 | return o_bestattack 298 | 299 | 300 | if __name__ == "__main__": 301 | 302 | model = MNISTModel("./models/mnist") 303 | 304 | attack = CarliniL2(model) 305 | 306 | (train_data, train_labels), (test_data, 307 | test_labels) = datasets.mnist.load_data() 308 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 309 | train_data = train_data[..., tf.newaxis] 310 | test_data = test_data[..., tf.newaxis] 311 | train_data = tf.cast(train_data, tf.float32) 312 | test_data = tf.cast(test_data, tf.float32) 313 | 314 | # inputs = train_data[25] # tf.Tensor[(28, 28, 1)] 315 | inputs = train_data[25:26] # tf.Tensor[(1, 28, 28, 1)] 316 | 317 | targets = np.eye(10)[9] 318 | print(targets) 319 | list_targets = [] 320 | list_targets.append(targets) 321 | 322 | timestart = time.time() 323 | adv = attack.attack(inputs, list_targets) 324 | timeend = time.time() 325 | 326 | print("Took", timeend - timestart, "seconds to run", len(inputs), "samples.") 327 | 328 | for i in range(len(adv)): 329 | print("Valid:") 330 | show(inputs[i]) 331 | print("Classification:", model.predict(inputs[i:i + 1])) 332 | 333 | print("Adversarial:") 334 | print(np.shape(adv[i])) 335 | show(adv[i]) 336 | 337 | adv[i] = adv[i][tf.newaxis, ...] 338 | print("Classification:", model.predict(adv[i:i + 1])) 339 | 340 | print("Total distortion:", np.sum((adv[i] - inputs[i])**2)**.5) 341 | -------------------------------------------------------------------------------- /l2_attack/mnist/checkpoint: -------------------------------------------------------------------------------- 1 | model_checkpoint_path: "trained_model" 2 | all_model_checkpoint_paths: "trained_model" 3 | -------------------------------------------------------------------------------- /l2_attack/mnist/trained_model.data-00000-of-00001: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/mnist/trained_model.data-00000-of-00001 -------------------------------------------------------------------------------- /l2_attack/mnist/trained_model.index: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/mnist/trained_model.index -------------------------------------------------------------------------------- /l2_attack/models/checkpoint: -------------------------------------------------------------------------------- 1 | model_checkpoint_path: "mnist" 2 | all_model_checkpoint_paths: "mnist" 3 | -------------------------------------------------------------------------------- /l2_attack/models/mnist.data-00000-of-00001: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/models/mnist.data-00000-of-00001 -------------------------------------------------------------------------------- /l2_attack/models/mnist.index: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MyRespect/AdversarialAttack/b63ebdeedfa0916e0efe5f76c5a6f3803eea8bdf/l2_attack/models/mnist.index -------------------------------------------------------------------------------- /l2_attack/test.py: -------------------------------------------------------------------------------- 1 | import time 2 | import numpy as np 3 | import tensorflow as tf 4 | 5 | from classifier import MNISTModel 6 | from attacker import CarliniL2 7 | from tensorflow.keras import datasets, Model, losses, optimizers, metrics 8 | 9 | 10 | def show(img): 11 | """ 12 | Show MNSIT digits in the console. 13 | """ 14 | img = np.array(img) 15 | 16 | remap = " .*#" + "#" * 100 17 | img = (img.flatten() + .5) * 3 18 | if len(img) != 784: 19 | return 20 | print("START") 21 | for i in range(28): 22 | print("".join([remap[int(round(x))] for x in img[i * 28:i * 28 + 28]])) 23 | 24 | 25 | if __name__ == "__main__": 26 | 27 | model = MNISTModel() 28 | model.load_weights("./mnist/trained_model") 29 | 30 | attack = CarliniL2(model) 31 | 32 | (train_data, train_labels), (test_data, 33 | test_labels) = datasets.mnist.load_data() 34 | train_data, test_data = train_data / 255.0 - 0.5, test_data / 255.0 - 0.5 35 | train_data = train_data[..., tf.newaxis] 36 | test_data = test_data[..., tf.newaxis] 37 | train_data = tf.cast(train_data, tf.float32) 38 | test_data = tf.cast(test_data, tf.float32) 39 | 40 | # inputs = train_data[25] # tf.Tensor[(28, 28, 1)] 41 | inputs = train_data[25:26] # tf.Tensor[(1, 28, 28, 1)] 42 | 43 | targets = np.eye(10)[9] 44 | print(targets) 45 | list_targets = [] 46 | list_targets.append(targets) 47 | 48 | timestart = time.time() 49 | adv = attack.attack(inputs, list_targets) 50 | timeend = time.time() 51 | 52 | print("Took", timeend - timestart, "seconds to run", len(inputs), "samples.") 53 | 54 | for i in range(len(adv)): 55 | print("Valid:") 56 | show(inputs[i]) 57 | print("Classification:", model.predict(inputs[i:i + 1])) 58 | 59 | print("Adversarial:") 60 | print(np.shape(adv[i])) 61 | show(adv[i]) 62 | 63 | adv[i] = adv[i][tf.newaxis, ...] 64 | print("Classification:", model.predict(adv[i:i + 1])) 65 | 66 | print("Total distortion:", np.sum((adv[i] - inputs[i])**2)**.5) 67 | --------------------------------------------------------------------------------