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segment-geospatial

segment-geospatial

Guides segment-geospatial/SamGeo workflows for geospatial SAM segmentation, SAM2/SAM3 model variants, REST API serving, raster/vector IO, and optional text or caption model integrations.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: segment-geospatial description: "Guides segment-geospatial/SamGeo workflows for geospatial SAM segmentation, SAM2/SAM3 model variants, REST API serving, raster/vector IO, and optional text or caption model integrations." disable-model-invocation: true metadata: disco-role: operating license: MIT

segment-geospatial (SamGeo)

Use this repo skill when a task involves the segment-geospatial package, the samgeo Python import, or geospatial image segmentation with SAM-family models. It is self-contained operating guidance distilled from package code, docs, examples, tests, and installed-package inspection for version 1.4.1.

First choose the route

User taskRead
Segment a GeoTIFF or image with SAM1/SAM2, automatic masks, point prompts, box prompts, or SAM2 videocore-segmentation
Use SAM3/SAM3.1, text prompts, point/box instance prompts, tiled large-image segmentation, batch images, or SAM3 video trackingsamgeo3-workflows
Download map tiles, handle CRS, prepare multi-band imagery, convert raster masks to vectors, split/merge rasters, inspect raster metadata, or use UTM helpersgeospatial-utilities
Use FastSAM, HQ-SAM, LangSAM/GroundingDINO text prompts, BLIP image captioning, or optional detectree2/FER notesspecialized-models
Serve segmentation over HTTP, call samgeo-api, validate API parameters, handle output formats, or troubleshoot model/image cachesapi-server

Read model-and-workflow-overview.md for the package map and installation-and-dependencies.md before choosing extras or CUDA packages. Read troubleshooting.md for cross-cutting install, GPU, model-download, CRS, and optional-dependency failures.

Minimal install and import checks

Use a fresh environment. Python 3.10-3.12 is exercised by the repository CI; Python 3.11 is a safe default for ML/geospatial dependencies.

pip install "segment-geospatial[samgeo2,samgeo3,fast,hq,text,api]"
python - <<'PY'
import samgeo
from samgeo.model_registry import AVAILABLE_MODELS
print(samgeo.__version__)
print(AVAILABLE_MODELS)
PY

For SAM3 runtime work, verify CUDA before promising a run:

import torch
print(torch.__version__, torch.version.cuda)
print(torch.cuda.is_available(), torch.cuda.device_count())

Run the bundled safe diagnostic when an environment looks questionable:

python scripts/check_install.py --check-optional
python scripts/check_install.py --require-cuda

The scripts only import modules and inspect lightweight API state; they do not download model weights or start a service.

Package entry points and outputs

  • Python import: samgeo.
  • Distribution: segment-geospatial.
  • CLI entry point: samgeo-api for the FastAPI service.
  • Main classes: SamGeo, SamGeo2, SamGeo3, SamGeo3Video, LangSAM, FastSAM/HQ-SAM wrappers, and ImageCaptioner.
  • Typical inputs: GeoTIFF, PNG/JPEG, NumPy arrays, URLs, point coordinates, bounding boxes, GeoJSON/vector prompts, and videos/time-series frames.
  • Typical outputs: mask GeoTIFF/PNG, vector GeoPackage/Shapefile/GeoJSON, JSON/detections from the API, caption/feature lists, and blended videos.

Operating rules

  • Do not tell users to open notebooks, scripts, tests, or docs from the original checkout. Use the bundled references and scripts in this skill.
  • Distinguish pixel coordinates from geographic coordinates. If points or boxes are in a CRS, pass point_crs or box_crs where the selected API supports it.
  • SamGeo preserves the source raster CRS during segmentation; it does not automatically reproject masks to EPSG:4326.
  • SAM3/SAM3.1 guidance should be treated as CUDA-backed unless the task is only inspecting imports or mock-backed tests. CPU import checks are not proof of real SAM3 runtime capability.
  • Model-weight downloads, Hugging Face authentication, map-tile downloads, long-running inference, notebooks, QGIS plugin operations, and detectree2 or GDAL-specific paths require explicit user/environment readiness.
  • The user requested not import for this generated skill run; do not run the repo-skill import helper unless a later instruction explicitly approves it.

Provenance and refresh

Read repo-provenance.md before deciding this skill matches a new checkout. If the commit, package version, public APIs, or major example/test paths differ, refresh the skill before relying on stale routing or API details.

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