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name: tiatoolbox description: "Route TIAToolbox tasks for computational pathology image I/O, preprocessing, model inference, annotations, visualization, CLI usage, and troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

TIAToolbox

Use this repo skill when a user asks about TIAToolbox, tiatoolbox, TIA Toolbox, computational pathology workflows, WSI reading, stain normalization, tissue masking, patch extraction, pretrained pathology models, annotation stores, visualization overlays, or the tiatoolbox command-line interface.

TIAToolbox is a Python package for digital pathology image analysis. It covers whole-slide image I/O, image preprocessing, model inference, annotation storage/querying, and visualization.

Quick Setup

Install the public package in a Python environment that matches TIAToolbox requirements:

python -m pip install tiatoolbox
python - <<'PY'
import tiatoolbox
print(tiatoolbox.__version__)
PY
tiatoolbox --help

If a task needs CPU-only Torch wheels or avoids GPU/CUDA packages, plan that before installing broad dependencies. Use cli-and-configuration troubleshooting when imports, native image codecs, OpenSlide, Torch, or the console entry point fail.

Route by Task

• Use sub-skills/wsi-io/SKILL.md for WSI/image readers, metadata, resolution units, thumbnails, tiles, multichannel images, read bounds, and registration setup.
• Use sub-skills/image-preprocessing/SKILL.md for tissue masks, stain normalization/extraction/augmentation, patch extraction, tile pyramids, and preprocessing checks before inference.
• Use sub-skills/model-inference/SKILL.md for patch prediction, feature extraction, semantic segmentation, nucleus detection, multitask segmentation, pretrained model keys, IO configs, devices, weights, and outputs.
• Use sub-skills/annotation-visualization/SKILL.md for AnnotationStore, SQLiteStore, DictionaryStore, DSL filters, GeoJSON/dat overlays, graph overlays, tile servers, visualization layouts, and port/overlay issues.
• Use sub-skills/cli-and-configuration/SKILL.md for console command discovery, shell-safe command construction, JSON/YAML quoting, install validation, device/backend selection, and CLI startup troubleshooting.

Common Workflows

• Read a WSI or image region: route to wsi-io; confirm input format, reader choice, resolution units, metadata availability, crop bounds, and memory-safe output size.
• Prepare image data: route to image-preprocessing; choose tissue mask method, stain normalizer, patch extractor mode, mask resolution, stride, and validation checks.
• Run pretrained or custom inference: route to model-inference; validate model key or custom model, avoid unwanted weight downloads, choose device, construct IO config, and decide output type.
• Inspect model outputs: route to annotation-visualization; validate annotation properties/geometry, filter expressions, overlay naming, color mapping, and server launch constraints.
• Build a command: route first to cli-and-configuration; then cross-link to the owning workflow sub-skill for data semantics and troubleshooting.

Safe Helper Scripts

Each sub-skill bundles helper scripts that future agents can run after TIAToolbox is installed:

• sub-skills/wsi-io/scripts/wsi_io_smoke.py checks tiny in-memory VirtualWSIReader behavior without WSI downloads.
• sub-skills/image-preprocessing/scripts/preprocessing_smoke.py checks maskers, stain normalizers, and patch extraction on tiny arrays.
• sub-skills/model-inference/scripts/model_registry_probe.py summarizes the installed pretrained model registry without importing models or downloading weights.
• sub-skills/annotation-visualization/scripts/annotation_store_smoke.py checks in-memory annotation stores without launching visualization servers.
• sub-skills/cli-and-configuration/scripts/cli_help_probe.py runs timeout-bounded tiatoolbox --help and subcommand help probes.

Troubleshooting First Moves

• For ModuleNotFoundError, tiatoolbox: command not found, native codec/OpenSlide failures, or CUDA/MPS/Torch mismatches, start with sub-skills/cli-and-configuration/references/troubleshooting.md.
• For incorrect crop sizes, missing objective power, unsupported WSI formats, or multichannel axis surprises, read sub-skills/wsi-io/references/troubleshooting.md.
• For zero patches, mask mismatch, invalid stain matrices, or stride/shape confusion, read sub-skills/image-preprocessing/references/troubleshooting.md.
• For model key typos, unexpected downloads, output-type mistakes, or deprecated nucleus instance segmentation APIs, read sub-skills/model-inference/references/troubleshooting.md.
• For overlay visibility, annotation filter errors, large annotation lag, or visualization port conflicts, read sub-skills/annotation-visualization/references/troubleshooting.md.

Freshness and Routing Metadata

• Read references/repo-provenance.md when deciding whether this skill is stale against a newer TIAToolbox checkout.
• references/repo-routing-metadata.json is structured metadata for the managed repo-skills-router import process.

Boundaries

This skill is for using TIAToolbox as a package and understanding its public workflows. For repository contribution tasks such as changing tests, packaging, release automation, Docker matrices, or benchmarks, prefer a Python repository-maintenance route instead of this user-facing TIAToolbox workflow skill.