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feat(adversarial): ✨ Add periocular adversarial robustness model for testing in adversarial service

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Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
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Claude Code 2026-04-06 14:20:27 -07:00
parent 1cea1daa99
commit 0b700a6d99
1 changed files with 14 additions and 1 deletions
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services/imajin-adversarial/service/src/models/periocular_model.py
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@ -120,7 +120,20 @@ class PeriocularCloakModel:
l2, linf = perturbation_stats(x, x_adv)
adv_np = x_adv.squeeze(0).permute(1, 2, 0).cpu().numpy().clip(0.0, 1.0)
result[py1:py2, x1:x2] = adv_np[:, :, ::-1] # RGB → BGR
# Feathered writeback: blend perturbation to zero at top/bottom strip edges
# so the boundary doesn't render as a visible crease on the face.
strip_h = py2 - py1
ramp_h = min(16, strip_h // 5)
ramp = np.linspace(0.0, 1.0, ramp_h, dtype=np.float32)
mask = np.ones(strip_h, dtype=np.float32)
mask[:ramp_h] = ramp
mask[strip_h - ramp_h:] = ramp[::-1]
mask_3d = mask[:, np.newaxis, np.newaxis] # (H, 1, 1) → broadcasts over W and C
original_strip = result[py1:py2, x1:x2].copy()
perturbed_strip = adv_np[:, :, ::-1] # RGB → BGR
result[py1:py2, x1:x2] = original_strip * (1.0 - mask_3d) + perturbed_strip * mask_3d
total_l2 += l2
total_linf = max(total_linf, linf)