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name: object-detection description: "Use MambaVision as an MMDetection Cascade Mask R-CNN backbone on COCO, with tiny/small/base configs, checkpoint path adaptation, train/test command planning, and OpenMMLab failure diagnosis." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

MambaVision Object Detection

Use this sub-skill for the published MambaVision object-detection setup: Cascade Mask R-CNN on COCO with the bundled detection configs and adapter.

Route here for

• choosing the tiny, small, or base detection config
• adapting backbone pretrained paths and detector checkpoint paths
• preparing COCO train/val annotation layout
• building single-GPU or Slurm train/test commands
• reading bbox and segm metrics from MMDetection output
• diagnosing MM_mamba_vision registry, import, version, and checkpoint issues

Route elsewhere

• classification checkpoints, model catalog, or ImageNet validation -> ../classification/SKILL.md
• ADE20K / MMSegmentation backbone use -> ../semantic-segmentation/SKILL.md
• generic MMDetection utility folders that are not MambaVision-specific -> do not treat them as this workflow

Start with:

• references/configuration.md
• references/backbone-adapter.md
• references/workflows.md
• references/troubleshooting.md
• scripts/print_mmdet_command.py

Safe preflight checks:

• python scripts/print_mmdet_command.py --help to inspect the bundled command-template helper.
• In the user's target MMDetection project, run the selected training/test entry point's --help before launching any heavy job.

This skill is a router and reference hub. It does not launch training jobs or download checkpoints on its own.