Upload fawkes_wrapper_gradio_v_1_0.py

fawkes_wrapper_gradio_v_1_0.py

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+# -*- coding: utf-8 -*-
+"""fawkes_wrapper_gradio_V_1.0
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1q9cDeedmQrsMwYqbulhSWs8Wk5ligIs-
+"""
+
+# fawkes_protection.py
+
+from fawkes.protection import Fawkes
+from fawkes.utils import Faces, reverse_process_cloaked
+from fawkes.differentiator import FawkesMaskGeneration
+import tensorflow as tf
+import numpy as np
+
+IMG_SIZE = 112
+PREPROCESS = 'raw'
+
+class FawkesProtection:
+    def __init__(self):
+        # Initialize Fawkes instances for different protection levels
+        self.fwks_l = Fawkes("extractor_2", '0', 1, mode='low')
+        self.fwks_m = Fawkes("extractor_2", '0', 1, mode='mid')
+        self.fwks_h = Fawkes("extractor_2", '0', 1, mode='high')
+
+    def generate_cloak_images(self, protector, image_X, target_emb=None):
+        cloaked_image_X = protector.compute(image_X, target_emb)
+        return cloaked_image_X
+
+    def predict(self, img, level, th=0.04, sd=1e7, lr=10, max_step=500, batch_size=1, format='png',
+                separate_target=True, debug=False, no_align=False, exp="", maximize=True,
+                save_last_on_failed=True):
+
+        img = img.convert('RGB')
+        img = tf.keras.utils.img_to_array(img)
+
+        if level == 'low':
+            fwks = self.fwks_l
+        elif level == 'mid':
+            fwks = self.fwks_m
+        elif level == 'high':
+            fwks = self.fwks_h
+
+        current_param = "-".join([str(x) for x in [fwks.th, sd, fwks.lr, fwks.max_step, batch_size, format,
+                                                   separate_target, debug]])
+        faces = Faces(['./Current Face'], [img], fwks.aligner, verbose=0, no_align=False)
+        original_images = faces.cropped_faces
+
+        if len(original_images) == 0:
+            raise Exception("No face detected. ")
+        original_images = np.array(original_images)
+
+        if current_param != fwks.protector_param:
+            fwks.protector_param = current_param
+            if fwks.protector is not None:
+                del fwks.protector
+            if batch_size == -1:
+                batch_size = len(original_images)
+            fwks.protector = FawkesMaskGeneration(fwks.feature_extractors_ls,
+                                                  batch_size=batch_size,
+                                                  mimic_img=True,
+                                                  intensity_range=PREPROCESS,
+                                                  initial_const=sd,
+                                                  learning_rate=fwks.lr,
+                                                  max_iterations=fwks.max_step,
+                                                  l_threshold=fwks.th,
+                                                  verbose=0,
+                                                  maximize=maximize,
+                                                  keep_final=False,
+                                                  image_shape=(IMG_SIZE, IMG_SIZE, 3),
+                                                  loss_method='features',
+                                                  tanh_process=True,
+                                                  save_last_on_failed=save_last_on_failed,
+                                                  )
+        protected_images = self.generate_cloak_images(fwks.protector, original_images)
+        faces.cloaked_cropped_faces = protected_images
+
+        final_images, _ = faces.merge_faces(
+            reverse_process_cloaked(protected_images, preprocess=PREPROCESS),
+            reverse_process_cloaked(original_images, preprocess=PREPROCESS))
+
+        return final_images[-1].astype(np.uint8)