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name: specialized-models description: "Routes SamGeo optional model integrations including FastSAM, HQ-SAM, LangSAM/GroundingDINO text prompts, BLIP captioning, detectree2 notes, and FER/GDAL gaps." disable-model-invocation: true metadata: disco-role: operating license: MIT

Specialized model integrations

Use this sub-skill for optional model families and auxiliary workflows that sit outside the primary SamGeo, SamGeo2, and SamGeo3 routes.

Read this when

• The user asks for FastSAM (samgeo.fast_sam) speed-oriented segmentation.
• The user asks for HQ-SAM (samgeo.hq_sam) high-quality masks.
• The user asks for LangSAM, GroundingDINO, or text prompts with SAM1/SAM2.
• The user asks for BLIP image captioning or extracting aerial features from a caption/image.
• The user asks about detectree2 tree crowns or FER/GDAL feature edge reconstruction and needs to know why those are optional/gap paths.

Route elsewhere

• Standard SAM1/SAM2 segmentation: core-segmentation.
• SAM3 text/prompt/video/tiled workflows: samgeo3-workflows.
• Raster/vector/CRS utilities: geospatial-utilities.
• HTTP API text/automatic/predict endpoints: api-server.

Before using optional models

1. Install only the extra needed for the workflow: [fast], [hq], [text], [samgeo3], or a selected combined set.
2. Run scripts/optional_model_imports.py before constructing models.
3. Confirm whether the workflow downloads model weights, Hugging Face assets, spaCy models, map tiles, or detectree2/Detectron2 dependencies.
4. Use one image/crop and save a simple mask before scaling to batches.

References and scripts

• model-overview.md compares FastSAM, HQ-SAM, LangSAM, captioning, detectree2, and FER support.
• workflows.md gives focused recipes for the optional workflows.
• troubleshooting.md covers optional import, model download, pkg_resources, GroundingDINO, BLIP/spaCy, detectree2, and GDAL issues.
• scripts/optional_model_imports.py checks optional imports without loading weights; caption import is opt-in because it performs a network vocabulary fetch.

Validation candidates

• FastSAM, HQ-SAM, LangSAM, and captioning example notebooks are evidence and optional native candidates; they require model/network readiness.
• detectree2 and FER are documented as optional gaps in this skill because the prepared environment did not install Detectron2/detectree2 or GDAL.