Individual skill
tao-train-mask-auto-label
MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".
skills/tao-train-mask-auto-label/SKILL.md
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- Last checked
- Nov 9, 2026
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- 3,909
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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- agent-skills Repository topic
- agentic-ai Repository topic
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- cuda Repository topic
- developer-tools Repository topic
- llm Repository topic
- omniverse Repository topic
- segmentation Declared skill tag
- engineering Derived category
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# MAL
> **Standalone install?** If this session was not initialized by the TAO skill bank plugin, run the `tao-setup` skill first (host preflight, credentials, cross-skill discovery).
MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (e.g., point or box annotations). Uses ViT-MAE backbone.
Set train.pretrained_model_path for ViT-MAE pretrained weights.
## Quick Start (docker run)
Docker-native launch — no TAO SDK and no Python on the host. Use the local
Docker/platform skill instead when it gives a stricter environment-specific
command (non-root UID mapping, cache redirects, remote daemons).
