open-edge-platform/anomalib

anomalib-adding-a-datamodule

Adds a new dataset/datamodule to anomalib under src/anomalib/data/. Use when wiring a new data source into the AnomalibDataset/AnomalibDataModule base classes, exporting it so anomalib.data.<Name> and the CLI/config (jsonargparse) can discover it, and adding…

원문 언어: 영어

models-data

Reviews anomalib model, data, callback, metric, and CLI integration conventions

원문 언어: 영어

ui-test-utils

Use when writing or updating Anomalib Studio UI component or hook tests that need the shared render/renderHook helpers, React Router paths or parameters, React Query, theme, URL-query, stream, suspense, or toast providers.

원문 언어: 영어

agentic-actions-auditor

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD…

원문 언어: 영어

anomalib-adding-a-model

Adds a new anomaly-detection model to anomalib under src/anomalib/models/. Use when implementing a new model architecture (image or video), wiring it into the AnomalibModule base class, registering it so get_model() and the CLI/config (jsonargparse) can…

원문 언어: 영어

anomalib-benchmarking

Runs the anomalib benchmarking pipeline to train/evaluate a grid of model + dataset (+ category) combinations and collect metrics into a results CSV. Use when comparing multiple models/datasets/categories in one sweep, or authoring/editing a benchmark config…

원문 언어: 영어

anomalib-tiled-ensemble

Runs and configures the anomalib tiled-ensemble pipeline, which trains/evaluates one model per image tile and merges results (with optional seam smoothing) for high-resolution anomaly detection. Use when the user wants to train with image tiling, mentions…

원문 언어: 영어

anomalib-training

Trains an anomalib model on a dataset via the Python API or CLI, including training on a custom folder-structured dataset with the Folder datamodule. Use when writing or debugging an anomalib training script/command, choosing Engine/Trainer arguments, or…

원문 언어: 영어

fastapi-rest-api-design

Designs and reviews REST APIs for FastAPI services using consistent resource naming, HTTP semantics, validation, security, and error handling patterns. Use for backend API tasks, endpoint design/refactors, or API review requests in FastAPI/Python projects.

원문 언어: 영어

benchmark-and-docs-refresh

Run or continue model benchmarks, collect measured results, and refresh README/docs benchmark sections from generated artifacts. Use when benchmark tables in model docs need to be created, updated, or corrected.

원문 언어: 영어

docs-changelog

Reviews anomalib docstrings, documentation updates, and changelog expectations

원문 언어: 영어

model-doc-sync

Keep anomalib model READMEs, docs pages, image assets, and benchmark/result references in sync

원문 언어: 영어

model-sample-image-export

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.

원문 언어: 영어

pr-workflow

Reviews anomalib contributor workflow, PR title, branch naming, and quality gate expectations

원문 언어: 영어

python-docstrings

Enforces Google-style Python docstrings for Python code

원문 언어: 영어

python-style

Reviews anomalib Python style, typing, imports, and public API conventions

원문 언어: 영어

testing

Review/generate unit, integration, and regression test expectations

원문 언어: 영어

third-party-code

Review/generate third-party code attribution, licensing, and notice requirements

원문 언어: 영어