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name: deepaugment_transform_proxy description: Create deterministic semantic-preserving texture and style perturbations for bounded DeepAugment-style recovery tests.

DeepAugment Transform Proxy

Use this skill when full DeepAugment image-to-image networks are unavailable but a bounded recovery must still exercise the paper mechanism: label-preserving changes to texture-like/local-statistic features. Do not use this skill as evidence of full ImageNet-scale DeepAugment training.

Inputs

• Examples with numeric features and a label.
• A deterministic seed and perturbation strength.

Outputs

• Augmented examples with unchanged labels.
• A transformation log naming the applied perturbation families.

Workflow

1. Keep semantic coordinates stable enough for the class label to remain valid.
2. Perturb nuisance or texture-like coordinates with contrast, noise, and mixture operations.
3. Emit a log for every generated example.
4. Verify transformed examples differ from clean inputs while preserving labels.

Validation

Run python tests/test_transform.py or the Distiller skill validator with tests enabled.

Limitations

The proxy operates on tiny numeric features, not real images or perturbed neural image translators. It is acceptable only for declared soft-mode reduced recovery.