- name
- model-sample-image-export
- description
- Export, validate, and publish model sample-result images into docs/source/images and reference them from README/docs pages. Use when model sample images are missing, outdated, or suspected to be invalid.
# Model Sample Image Export
Use this skill to create or refresh sample-result images for model documentation.
## Scope
This skill focuses on:
- selecting completed trained checkpoints or finished benchmark runs
- exporting prediction/sample images
- copying or saving them into `docs/source/images/<model>/results/`
- updating README/docs sample-result references
- rejecting broken or misleading outputs
It does not own benchmark table maintenance. Use `benchmark-and-docs-refresh` for that.
## Request changes when
- sample images come from incomplete or untrusted runs;
- published outputs are clearly degenerate or misleading;
- README or docs references point to missing image files;
- the docs surface implies three valid examples when fewer trustworthy outputs exist.
## Required Source Quality
Only use sample images from:
- completed trained checkpoints
- completed benchmark runs with valid prediction outputs
- finished model outputs that can be traced back to a real run artifact
- if no suitable completed checkpoint, benchmark output, or other traceable run artifact exists, schedule a few runs to generate trustworthy sample images
Do not use:
- incomplete runs
- partially written checkpoints
- outputs with empty/degenerate masks
- outputs driven by NaNs or obviously broken predictions
## Required Workflow
1. Identify candidate checkpoints/runs in `results/`.
2. Verify the run is complete enough to trust.
3. If verification fails, schedule a few runs to train the model on a few categories.
4. Generate predictions from the checkpoint/run.
5. Inspect output quality before publishing images.
6. Save the selected images into `docs/source/images/<model>/results/`.
7. Update README/docs references.
## Preferred Output Layout
- `docs/source/images/<model>/results/0.png`
- `docs/source/images/<model>/results/1.png`
- `docs/source/images/<model>/results/2.png`
If you have fewer than 3 trustworthy images, train the model on a few more categories to generate more sample images.
## README Update Pattern
Preferred pattern:
```md
### Sample Results

```
Repeat for additional images.
## Docs Update Pattern
Preferred docs-page pattern:
````md
## Sample Results
```{eval-rst}
.. image:: ../../../../../images/<model>/results/0.png
```
````
## Validation Rules
Before publishing an image:
1. Check that the referenced file exists.
2. Check that the image is visually plausible.
3. Check that the mask/anomaly region is not obviously wrong.
4. Check that the sample came from a trained or otherwise valid completed run.
5. If a model/category output is degenerate, exclude it and say so explicitly.
## Reviewer checklist
- Check run completeness.
- Check image quality.
- Check exported file existence.
- Check README and docs references.
## Repo-Specific Notes
- In this repo, some completed checkpoints can still produce bad masks.
- If generic visualization helpers fail, derive a narrow exporter for the specific model/run.
- Keep exporter scripts focused and traceable to the chosen checkpoints.
- When in doubt, prefer fewer trustworthy sample images over a full set of misleading ones.
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