Added support for SNAL attack #2440
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## dev_1.19.0 #2440 +/- ##
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+ Coverage 85.25% 85.38% +0.13%
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Files 330 333 +3
Lines 30470 30930 +460
Branches 5228 5294 +66
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+ Hits 25977 26410 +433
- Misses 3042 3053 +11
- Partials 1451 1467 +16
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![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
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Hi @CNOCycle Thank you very much for you pull request. I think it looks good, I have only found a few formatting and documentation issues. Could you please take a look and let me know if you have questions?
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| # | |||
| # Copyright (C) The Adversarial Robustness Toolbox (ART) Authors 2018 | |||
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| # Copyright (C) The Adversarial Robustness Toolbox (ART) Authors 2018 | |
| # Copyright (C) The Adversarial Robustness Toolbox (ART) Authors 2024 |
| """ | ||
| This module implements the paper: "Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks" | ||
| | Paper link: https://arxiv.org/abs/2304.05370 | ||
| """ |
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| """ | |
| This module implements the paper: "Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks" | |
| | Paper link: https://arxiv.org/abs/2304.05370 | |
| """ | |
| """ | |
| This module implements the paper: "Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks" | |
| | Paper link: https://arxiv.org/abs/2304.05370 | |
| """ |
| import logging | ||
| from typing import Optional, Tuple, TYPE_CHECKING |
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| import logging | |
| from typing import Optional, Tuple, TYPE_CHECKING | |
| import logging | |
| import random | |
| from typing import Optional, Tuple, TYPE_CHECKING |
| from typing import Optional, Tuple, TYPE_CHECKING | ||
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| import numpy as np | ||
| import random |
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| import random |
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| x_out[:, :, y1:y2, x1:x2] = updated | ||
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| return x_out, tile_mat |
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Add empty line at end of file
| return x_out, tile_mat | |
| return x_out, tile_mat | |
| import torch | ||
| TRIAL = 10 |
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| import torch | |
| TRIAL = 10 | |
| import torch | |
| TRIAL = 10 |
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| def __init__( | ||
| self, | ||
| estimator: "torch.nn.Module", |
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| estimator: "torch.nn.Module", | |
| estimator: PYTORCH_OBJECT_DETECTION_TYPE, |
and please add
PYTORCH_OBJECT_DETECTION_TYPE = Union[PyTorchObjectDetector]to art/utils.py with the other type definitions at the tope of that file.
| # pylint: disable=C0412 | ||
| import torch | ||
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| logger = logging.getLogger(__name__) |
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Could you please add docstrings to all functions in this module?
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| logger = logging.getLogger(__name__) | ||
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| def _bbox_ioa(box1: "torch.tenosr", |
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Could you please include the license text of the file yolov5/utils/metrics.py to this docstring?
| block_size: int): | ||
| """ | ||
| === NOTE === | ||
| This function is modified from torchvision (torchvision/ops/drop_block.py) |
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Could you please include the license text of the file yolov5/utils/metrics.py to this docstring?
art/attacks/evasion/steal_now_attack_later/steal_now_attack_later.py
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Hi @CNOCycle Thank you very much for your contribution of the SNAL attack to ART! |
Description
This pull request adds the support of the SNAL Attack proposed in [1].
[1]Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks. [Paper]
Fixes # (issue)
Type of change
Please check all relevant options.
Testing
Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.
Test Configuration:
Checklist