ResearchPapers/fawkes
ResearchPapers/fawkes
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Merge branch 'master' of https://github.com/Shawn-Shan/fawkes

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Shawn-Shan 2020-07-23 12:54:14 -05:00
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evaluation/README.md
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@ -10,7 +10,7 @@ Evaluation with Local Model
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. 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.
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). 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).
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.) 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.)
The script will output the protection success rate at the end. The script will output the protection success rate at the end.