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API: Inspect

This page documents raw input inspection utilities (patch checks) used before model inference.

Related pages:

inspect_provider_patch(
    *,
    spatial: SpatialSpec,
    temporal: Optional[TemporalSpec] = None,
    sensor: SensorSpec,
    backend: str = "gee",
    name: str = "gee_patch",
    value_range: Optional[Tuple[float, float]] = None,
    return_array: bool = False,
) -> Dict[str, Any]

Provider-agnostic patch inspection utility (recommended entry point). Use this when you want the same inspection flow but with a non-GEE provider backend.

inspect_gee_patch

inspect_gee_patch(
    *,
    spatial: SpatialSpec,
    temporal: Optional[TemporalSpec] = None,
    sensor: SensorSpec,
    backend: str = "gee",
    name: str = "gee_patch",
    value_range: Optional[Tuple[float, float]] = None,
    return_array: bool = False,
) -> Dict[str, Any]

Backwards-compatible GEE-focused wrapper around inspect_provider_patch(...) (compatibility wrapper). New code should prefer inspect_provider_patch(...) unless you specifically want the older GEE-focused name. It performs the same input quality checks (without running the model).

Returns

  • A JSON-serializable dict:
  • ok: bool
  • report: stats/check report
  • sensor, temporal, backend
  • artifacts: optional quicklook save paths
  • If return_array=True, includes array_chw (numpy array, not JSON-serializable)

Example

from rs_embed import inspect_gee_patch, PointBuffer, TemporalSpec, SensorSpec

rep = inspect_gee_patch(
    spatial=PointBuffer(121.5, 31.2, 2048),
    temporal=TemporalSpec.range("2022-06-01", "2022-09-01"),
    sensor=SensorSpec(
        collection="COPERNICUS/S2_SR_HARMONIZED",
        bands=("B4", "B3", "B2"),
        scale_m=10,
        cloudy_pct=30,
        composite="median",
        check_input=True,
        check_save_dir="artifacts",
    ),
    return_array=False,
)