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project_ipg

Object Detection
PyTorch
ONNX
adversarial-patches
yolov5
security
red-team
anima
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[IPG] Export adversarial patches — pth + safetensors + ONNX + TRT

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  1. README.md +64 -0
  2. all_patches.safetensors +3 -0
  3. export_manifest.json +265 -0
  4. onnx/patch_00.onnx +3 -0
  5. onnx/patch_01.onnx +3 -0
  6. onnx/patch_02.onnx +3 -0
  7. onnx/patch_03.onnx +3 -0
  8. onnx/patch_04.onnx +3 -0
  9. onnx/patch_05.onnx +3 -0
  10. onnx/patch_06.onnx +3 -0
  11. onnx/patch_07.onnx +3 -0
  12. onnx/patch_08.onnx +3 -0
  13. onnx/patch_09.onnx +3 -0
  14. onnx/patch_10.onnx +3 -0
  15. onnx/patch_11.onnx +3 -0
  16. onnx/patch_12.onnx +3 -0
  17. onnx/patch_13.onnx +3 -0
  18. onnx/patch_14.onnx +3 -0
  19. onnx/patch_15.onnx +3 -0
  20. onnx/patch_16.onnx +3 -0
  21. onnx/patch_17.onnx +3 -0
  22. onnx/patch_18.onnx +3 -0
  23. onnx/patch_19.onnx +3 -0
  24. onnx/patch_20.onnx +3 -0
  25. onnx/patch_21.onnx +3 -0
  26. onnx/patch_22.onnx +3 -0
  27. onnx/patch_23.onnx +3 -0
  28. onnx/patch_24.onnx +3 -0
  29. pth/patch_00.pt +3 -0
  30. pth/patch_01.pt +3 -0
  31. pth/patch_02.pt +3 -0
  32. pth/patch_03.pt +3 -0
  33. pth/patch_04.pt +3 -0
  34. pth/patch_05.pt +3 -0
  35. pth/patch_06.pt +3 -0
  36. pth/patch_07.pt +3 -0
  37. pth/patch_08.pt +3 -0
  38. pth/patch_09.pt +3 -0
  39. pth/patch_10.pt +3 -0
  40. pth/patch_11.pt +3 -0
  41. pth/patch_12.pt +3 -0
  42. pth/patch_13.pt +3 -0
  43. pth/patch_14.pt +3 -0
  44. pth/patch_15.pt +3 -0
  45. pth/patch_16.pt +3 -0
  46. pth/patch_17.pt +3 -0
  47. pth/patch_18.pt +3 -0
  48. pth/patch_19.pt +3 -0
  49. pth/patch_20.pt +3 -0
  50. pth/patch_21.pt +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - adversarial-patches
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+ - object-detection
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+ - yolov5
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+ - security
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+ - red-team
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+ - anima
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+ library_name: pytorch
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+ pipeline_tag: object-detection
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+ ---
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+
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+ # IPG — Incremental Patch Generation
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+
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+ Adversarial patches trained against YOLOv5l6 on MS COCO 2017 using the
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+ IPG method (arXiv:2508.10946).
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+
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+ ## Model Description
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+
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+ This repository contains 25 adversarial patches (64×64 pixels)
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+ optimized to reduce object detection confidence using the hiding attack objective.
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+
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+ ## Available Formats
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+
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+ | Format | Directory | Description |
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+ |--------|-----------|-------------|
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+ | PyTorch (.pt) | `pth/` | Full checkpoint with training history |
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+ | SafeTensors | `safetensors/` | Optimized tensor format |
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+ | Combined SafeTensors | `all_patches.safetensors` | All patches in one file |
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+ | ONNX | `onnx/` | Cross-platform inference |
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+ | TensorRT FP16 | `trt_fp16/` | NVIDIA optimized (half precision) |
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+ | TensorRT FP32 | `trt_fp32/` | NVIDIA optimized (full precision) |
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+
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+ ## Usage
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+
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+ ```python
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+ from safetensors.torch import load_file
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+
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+ # Load single patch
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+ data = load_file("safetensors/patch_00.safetensors")
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+ patch = data["patch"] # [3, 64, 64]
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+
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+ # Load all patches
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+ all_data = load_file("all_patches.safetensors")
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+ patches = [all_data[f"patch_{i:02d}"] for i in range(25)]
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+ ```
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+
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+ ## Training Details
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+
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+ - **Detector**: YOLOv5l6u
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+ - **Dataset**: MS COCO 2017 (20% accessible subset, ~23K images)
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+ - **Patches**: 25 × 200 epochs
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+ - **Patch size**: 64×64
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+ - **Optimizer**: Adam, lr=0.2, StepLR(50, γ=0.266)
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+ - **Hardware**: NVIDIA L4 23GB
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+ - **Training time**: 11.7h
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+
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+ ## Part of ANIMA
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+
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+ This module is part of the [ANIMA](https://github.com/RobotFlow-Labs) security layer
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+ for adversarial robustness testing.
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+
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+ Built with ANIMA by Robot Flow Labs.
all_patches.safetensors ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:2bd00a779b707affbe3530ea4a870f7156db81cd7b609d64079832619c832469
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+ size 1230832
export_manifest.json ADDED
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+ "pth",
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+ "onnx",
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+ "trt_fp16",
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+ "trt_fp32"
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+ ],
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+ "onnx": "/mnt/artifacts-datai/exports/project_ipg/onnx/patch_00.onnx",
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+ "trt_fp16": "/mnt/artifacts-datai/exports/project_ipg/trt_fp16/patch_00.engine",
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+ "trt_fp32": "/mnt/artifacts-datai/exports/project_ipg/trt_fp32/patch_00.engine"
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