├── adversarial-patch-object-detection.ipynb
└── readme.md


/readme.md:
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 1 | # On Physical Adversarial Patches for Object Detection
 2 | 
 3 | Code for https://arxiv.org/pdf/1906.11897.pdf.
 4 | 
 5 | Warning: this code is old and mainly experimental.
 6 | 
 7 | The yolov3 implementation used is [here](https://github.com/eriklindernoren/PyTorch-YOLOv3/tree/96d02089fedb7dd3003997199ee5bdf6b38fcd02). The following diff should be applied to the yolov3 code in order to run properly:
 8 | ```
 9 | diff --git a/models.py b/models.py
10 | index 1c9ba57..5a57b4c 100644
11 | --- a/models.py
12 | +++ b/models.py
13 | @@ -173,7 +173,13 @@ class YOLOLayer(nn.Module):
14 | 
15 |              nProposals = int((pred_conf > 0.5).sum().item())
16 |              recall = float(nCorrect / nGT) if nGT else 1
17 | -            precision = float(nCorrect / nProposals)
18 | +            # precision = float(nCorrect / nProposals)
19 | +            if nProposals:
20 | +                precision = float(nCorrect / nProposals)
21 | +            elif nCorrect:
22 | +                precision = 0
23 | +            else:
24 | +                precision = 1
25 | 
26 |              # Handle masks
27 |              mask = Variable(mask.type(ByteTensor))
28 | ```
29 | 


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