---

name: inference-and-evaluation description: "Run and troubleshoot YOLOv7-d2 PyTorch demo inference, visualization, W&B logging, benchmark planning, and COCO evaluation workflows." metadata: disco-role: operating disable-model-invocation: true license: GPL 3.0

Inference and Evaluation

Use this sub-skill when the user needs a YOLOv7-d2 PyTorch checkpoint demo, image/video visualization, confidence/NMS tuning, W&B inference logging, benchmark planning, COCO evaluation, or demo/eval troubleshooting.

Start here

1. Confirm the user has a config file, checkpoint/weights, and input images/video or a registered validation dataset.
2. Use scripts/check_demo_inputs.py to preflight config, input, output, and local weight paths.
3. Build a demo command with scripts/build_demo_command.py, then read references/workflows.md.
4. For evaluation or benchmark tasks, read references/evaluation.md.
5. For predictor internals and flags, read references/api-reference.md.
6. Use references/troubleshooting.md for headless OpenCV, missing weights, dataset registration, or LazyConfig demo issues.

Common command shapes

Image or directory demo:

python demo.py --config-file path/to/config.yaml --input path/to/image_or_dir --output path/to/out_dir --opts MODEL.WEIGHTS path/to/model.pth

Force CPU for a small smoke run:

python demo.py --config-file path/to/config.yaml --input path/to/image.jpg --output path/to/out.jpg --opts MODEL.WEIGHTS path/to/model.pth MODEL.DEVICE cpu

COCO evaluation shape:

python train_det.py --config-file path/to/config.yaml --eval-only MODEL.WEIGHTS path/to/model.pth

Boundaries

• For config selection, dataset registration, and training launchers, read ../training-and-configuration/SKILL.md.
• For ONNXRuntime inference rather than PyTorch checkpoint inference, read ../deployment-and-export/SKILL.md.

Safety notes

Do not run demos without user-provided weights and input data. Do not run the benchmark loop as a default check; it repeats inference and is hardware/model dependent. Do not run data-cleaning workflows without explicit user approval because they can influence which data is kept or discarded.