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Update README.md
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@ -10,7 +10,7 @@ Evaluation with Local Model
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To evaluate using local model, you are highly recommended to have a GPU device and train the model on it. Otherwise, the evaluation will be extremely slow and might even damage the CPUs on some machine.
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To evaluate using local model, you are highly recommended to have a GPU device and train the model on it. Otherwise, the evaluation will be extremely slow and might even damage the CPUs on some machine.
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To evaluate, run `python3 eval_local.py -d IMAGE_DIR`. Where `IMAGE_DIR` is the image directory send to Fawkes protection code, and it must contain both original images (testing) and cloaked image (training).
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To evaluate, run `python3 eval_local.py -d IMAGE_DIR`. Where `IMAGE_DIR` is the image directory send to Fawkes protection code, and it must contain both original images (testing) and cloaked image (training).
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All images in the directory must belong to the same person and have at least 10 images in them. Also, you cannot turn on `--seperate-target` during the protection. (We are working on reducing some of these limitations.)
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All images in the directory must belong to the same person and have at least 10 images in them. Also, you cannot turn on `--separate-target` during the protection. (We are working on reducing some of these limitations.)
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The script will output the protection success rate at the end.
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The script will output the protection success rate at the end.
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