1. correct a typo

2. rewrite distance function to remove sklearn


Former-commit-id: a9e6234a80e371b559750654fc60f3b1642eb74a [formerly d2dc50e6357b516398beb374a032b7cc2f169d70]
Former-commit-id: 3e566674f17cca4b89afe4d1fecfe1009c8166b8

fawkes/protection.py

@@ -102,26 +102,26 @@ class Fawkes(object):
 
         faces = Faces(image_paths, self.sess, verbose=1)
 
-        orginal_images = faces.cropped_faces
-        orginal_images = np.array(orginal_images)
+        original_images = faces.cropped_faces
+        original_images = np.array(original_images)
 
         if separate_target:
             target_embedding = []
-            for org_img in orginal_images:
+            for org_img in original_images:
                 org_img = org_img.reshape([1] + list(org_img.shape))
                 tar_emb = select_target_label(org_img, self.feature_extractors_ls, self.fs_names)
                 target_embedding.append(tar_emb)
             target_embedding = np.concatenate(target_embedding)
         else:
-            target_embedding = select_target_label(orginal_images, self.feature_extractors_ls, self.fs_names)
+            target_embedding = select_target_label(original_images, self.feature_extractors_ls, self.fs_names)
 
-        protected_images = generate_cloak_images(self.sess, self.feature_extractors_ls, orginal_images,
+        protected_images = generate_cloak_images(self.sess, self.feature_extractors_ls, original_images,
                                                  target_emb=target_embedding, th=th, faces=faces, sd=sd,
                                                  lr=lr, max_step=max_step, batch_size=batch_size)
 
         faces.cloaked_cropped_faces = protected_images
 
-        cloak_perturbation = reverse_process_cloaked(protected_images) - reverse_process_cloaked(orginal_images)
+        cloak_perturbation = reverse_process_cloaked(protected_images) - reverse_process_cloaked(original_images)
         final_images = faces.merge_faces(cloak_perturbation)
 
         for p_img, cloaked_img, path in zip(final_images, protected_images, image_paths):
@@ -129,7 +129,7 @@ class Fawkes(object):
             dump_image(p_img, file_name, format=format)
 
         elapsed_time = time.time() - start_time
-        print('attack cost %f s' % (elapsed_time))
+        print('attack cost %f s' % elapsed_time)
         print("Done!")
 
 

fawkes/utils.py

@@ -25,7 +25,6 @@ from keras.layers import Dense, Activation
 from keras.models import Model
 from keras.preprocessing import image
 from skimage.transform import resize
-from sklearn.metrics import pairwise_distances
 
 from fawkes.align_face import align, aligner
 from six.moves.urllib.request import urlopen
@@ -422,11 +421,27 @@ def extractor_ls_predict(feature_extractors_ls, X):
     return concated_feature_ls
 
 
+def pairwise_l2_distance(A, B):
+    BT = B.transpose()
+    vecProd = np.dot(A, BT)
+    SqA = A ** 2
+    sumSqA = np.matrix(np.sum(SqA, axis=1))
+    sumSqAEx = np.tile(sumSqA.transpose(), (1, vecProd.shape[1]))
+
+    SqB = B ** 2
+    sumSqB = np.sum(SqB, axis=1)
+    sumSqBEx = np.tile(sumSqB, (vecProd.shape[0], 1))
+    SqED = sumSqBEx + sumSqAEx - 2 * vecProd
+    SqED[SqED < 0] = 0.0
+    ED = np.sqrt(SqED)
+    return ED
+
+
 def calculate_dist_score(a, b, feature_extractors_ls, metric='l2'):
     features1 = extractor_ls_predict(feature_extractors_ls, a)
     features2 = extractor_ls_predict(feature_extractors_ls, b)
 
-    pair_cos = pairwise_distances(features1, features2, metric)
+    pair_cos = pairwise_l2_distance(features1, features2)
     max_sum = np.min(pair_cos, axis=0)
     max_sum_arg = np.argsort(max_sum)[::-1]
     max_sum_arg = max_sum_arg[:len(a)]
@@ -447,7 +462,7 @@ def select_target_label(imgs, feature_extractors_ls, feature_extractors_names, m
     embs = [p[1] for p in items]
     embs = np.array(embs)
 
-    pair_dist = pairwise_distances(original_feature_x, embs, metric)
+    pair_dist = pairwise_l2_distance(original_feature_x, embs)
     max_sum = np.min(pair_dist, axis=0)
     max_id = np.argmax(max_sum)
 

setup.py

@@ -82,8 +82,7 @@ install_requires = [
     'keras==2.2.5',
     'scikit-image',
     'pillow>=7.0.0',
-    'opencv-python>=4.2.0.34',
-    'sklearn',
+    'opencv-python>=4.2.0.34'
 ]
 
 setup(