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from fawkes.protection import Fawkes |
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from fawkes.utils import Faces, reverse_process_cloaked |
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from fawkes.differentiator import FawkesMaskGeneration |
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from keras import utils |
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import numpy as np |
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import gradio as gr |
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import spaces |
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IMG_SIZE = 112 |
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PREPROCESS = "raw" |
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def get_extractors(): |
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hash_map = { |
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"extractor_2": "ce703d481db2b83513bbdafa27434703", |
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"extractor_0": "94854151fd9077997d69ceda107f9c6b", |
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} |
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for key, value in hash_map.items(): |
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utils.get_file( |
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fname="{}.h5".format(key), |
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origin="http://mirror.cs.uchicago.edu/fawkes/files/{}.h5".format(key), |
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md5_hash=value, |
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cache_subdir="model", |
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) |
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def generate_cloak_images(protector, image_X, target_emb=None): |
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cloaked_image_X = protector.compute(image_X, target_emb) |
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return cloaked_image_X |
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def preproc(img): |
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img = img.convert("RGB") |
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img = utils.img_to_array(img) |
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return img |
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@spaces.GPU |
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def predict( |
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img, |
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level, |
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sd=1e7, |
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format="png", |
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separate_target=True, |
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debug=False, |
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maximize=True, |
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save_last_on_failed=True, |
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progress=gr.Progress(track_tqdm=True), |
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): |
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img = preproc(img) |
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if level == "low": |
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fwks = Fawkes("extractor_2", 1, mode="low") |
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elif level == "mid": |
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fwks = Fawkes("extractor_2", 1, mode="mid") |
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elif level == "high": |
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fwks = Fawkes("extractor_2", 1, mode="high") |
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current_param = "-".join( |
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[ |
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str(x) |
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for x in [ |
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fwks.th, |
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sd, |
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fwks.lr, |
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fwks.max_step, |
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-1, |
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format, |
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separate_target, |
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debug, |
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] |
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] |
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) |
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faces = Faces(["./Current Face"], [img], fwks.aligner, verbose=0, no_align=False) |
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original_images = faces.cropped_faces |
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if len(original_images) == 0: |
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raise Exception("No face detected. ") |
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original_images = np.array(original_images) |
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if current_param != fwks.protector_param: |
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fwks.protector_param = current_param |
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if fwks.protector is not None: |
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del fwks.protector |
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batch_size = len(original_images) |
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fwks.protector = FawkesMaskGeneration( |
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fwks.feature_extractors_ls, |
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batch_size=batch_size, |
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mimic_img=True, |
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intensity_range=PREPROCESS, |
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initial_const=sd, |
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learning_rate=fwks.lr, |
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max_iterations=fwks.max_step, |
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l_threshold=fwks.th, |
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verbose=0, |
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maximize=maximize, |
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keep_final=False, |
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image_shape=(IMG_SIZE, IMG_SIZE, 3), |
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loss_method="features", |
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tanh_process=True, |
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save_last_on_failed=save_last_on_failed, |
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) |
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protected_images = generate_cloak_images(fwks.protector, original_images) |
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faces.cloaked_cropped_faces = protected_images |
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final_images, _ = faces.merge_faces( |
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reverse_process_cloaked(protected_images, preprocess=PREPROCESS), |
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reverse_process_cloaked(original_images, preprocess=PREPROCESS), |
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) |
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return final_images[-1].astype(np.uint8) |
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get_extractors() |
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gr.Interface( |
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fn=predict, |
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inputs=[ |
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gr.components.Image(type="pil"), |
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gr.components.Radio(["low", "mid", "high"], label="Protection Level"), |
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], |
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outputs=gr.components.Image(type="pil"), |
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allow_flagging="never", |
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).launch(show_error=True, quiet=False) |
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