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21 lines
1.1 KiB
Markdown
21 lines
1.1 KiB
Markdown
Fawkes Evaluation
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We offer two ways to test the protection is effective, 1) train a local face recognition model using transfer learning, 2) use Microsoft Azure API.
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Note that we can't guarantee the protection is always successful due to new development in face recognition technique.
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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, 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 `--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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Evaluation with Microsoft Azure
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forthcoming...
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