---

name: "export-convert" description: "Guides AdelaiDet checkpoint key conversion, optimizer stripping, FCOS/BlendMask weight migration, ONNX export, and optional deployment-runtime caveats." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

export-convert

Use this sub-skill when a task asks to convert AdelaiDet checkpoints, rename FCOS/BlendMask keys, remove optimizer state, export an AdelaiDet model to ONNX, or reason about optional Caffe/NCNN/TensorRT deployment paths.

Use this route for

• Migrating official FCOS weights to AdelaiDet/Detectron2 key names.
• Renaming BlendMask centerness keys to ctrness.
• Stripping checkpoint optimizer/training state for smaller inference files.
• Building safe ONNX export commands for FCOS/BlendMask/CondInst-style models.
• Explaining why source Caffe/NCNN/TensorRT shell scripts are reference-only unless external runtimes are prepared.

Do not use this route for

• Installing or building adet._C. Use ../setup-build/SKILL.md.
• Choosing training configs or launching evaluation. Use ../train-eval/SKILL.md.
• Image/video demos from PyTorch checkpoints. Use ../demo-visualize/SKILL.md.
• Dataset preparation. Use ../data-prep/SKILL.md.
• Text-specific recognition/evaluation protocol. Use ../text-spotting/SKILL.md.

Read first

• references/export-and-checkpoints.md for checkpoint utility behavior.
• references/onnx-export.md for export constraints and optional runtime validation.
• ../../references/compatibility.md before mixing export tools with a different PyTorch/Detectron2 stack.

Skill-owned scripts

• scripts/convert_fcos_weight.py — convert official FCOS ResNet/FPN naming into AdelaiDet/Detectron2 naming.
• scripts/rename_blendmask_weights.py — rename BlendMask centerness keys to ctrness.
• scripts/strip_checkpoint_optimizer.py — save only the model state from a checkpoint.
• scripts/export_onnx.py — validated wrapper around the repository ONNX exporter.

Typical workflow

1. Confirm base setup with ../../scripts/check_install.py --cuda-ops.

2. For checkpoint key errors, run the relevant small conversion script on a copy of the checkpoint.

3. For ONNX export, dry-run first:

   python scripts/export_onnx.py --repo-root /path/to/AdelaiDet \
     --config configs/FCOS-Detection/R_50_1x.yaml \
     --weights /path/to/model.pth --output output/model.onnx --dry-run
   

4. Remove --dry-run only after config, weights, device, and output path are correct.

5. Validate exported ONNX with the runtime stack required by the downstream target; do not assume Caffe/NCNN/TensorRT are installed.

Decision points

• If checkpoint loading fails during training/eval, fix key naming here then return to train-eval.
• If ONNX export fails at model build/config import, return to setup-build or train-eval depending on the traceback.
• If deployment asks for Caffe, NCNN, TensorRT, or ONNXRuntime comparison, treat that as an expanded environment task with external dependencies and artifacts.