DatasetEnum
Built-in imagery configurations available for RasterFlow mosaic creation.Values
str
National Agriculture Imagery Program aerial imagery at 30 cm resolution, with red, green, blue, and near-infrared bands.
str
National Agriculture Imagery Program aerial imagery at 60 cm resolution, with red, green, blue, and near-infrared bands.
str
Sentinel-2 L2A composite that selects the closest valid observation for each pixel within the requested time window. Provides B02, B03, B04, and B08 at 10 m resolution.
str
Sentinel-2 L2A median composite for a latitude-based harvest-season window. Provides the B02, B03, B04, and B08 bands at 10 m resolution, plus an
N_VALID_PIXELS band.str
Sentinel-2 L2A median composite for a latitude-based planting-season window. Provides the B02, B03, B04, and B08 bands at 10 m resolution, plus an
N_VALID_PIXELS band.str
Sentinel-2 L2A median composite within the requested time window. Provides B02, B03, B04, and B08 at 10 m resolution.
str
Sentinel-2 L2A median composite within the requested time window. Provides all 12 L2A surface-reflectance bands, resampled to 10 m resolution.
DistanceMetricEnum
Distance metrics for comparing embedding vectors across time.Values
str
Dequantize and normalize AlphaEarth int8 embeddings before computing cosine distance.
str
Compute one minus the cosine similarity of normalized embedding vectors.
str
Compute straight-line distance between embedding vectors.
GeometryActorEnum
Model task types that produce georeferenced geometries from raster inputs.Values
str
Detect objects described by text prompts and return bounding-box geometries.
str
Detect objects described by text prompts and return polygon geometries.
GeometryModelRecipes
Preconfigured RasterFlow model recipes for text-prompted geometry outputs.Values
str
Detect objects described by text prompts in 30 cm NAIP imagery and return georeferenced bounding boxes with confidence scores.
str
Detect objects described by text prompts in 30 cm NAIP imagery and return georeferenced polygon geometries with confidence scores.
GeometryOutput
InferenceConfig
MergeModeEnum
Methods for assembling predictions from image patches.Values
str
Remove the configured border from each patch before assembling predictions.
str
Assemble patch predictions without overlap-specific clipping or blending.
str
Blend overlapping patch predictions with spatial weights to reduce seams.
ModelRecipes
Preconfigured RasterFlow model recipes for raster prediction outputs.Values
str
Detect rural roads in 1 m NAIP imagery with ChesapeakeRSC semantic segmentation.
str
Detect agricultural fields and field boundaries with Fields of the World, using Sentinel-2 planting- and harvest-season composites.
str
Estimate tree canopy height in meters from 60 cm NAIP RGB imagery with Meta CHM v1.
str
Detect sidewalks, roads, and crosswalks in 30 cm NAIP RGB imagery with Tile2Net semantic segmentation.
MosaicResult
Result for workflows that produce a mosaic index.Attributes
any
URI of the mosaic index GeoParquet output.
any
URI of the first mosaic store referenced by the index, when available.
any
Lazily loaded GeoDataFrame read from
mosaic_index_uri. Requires GeoPandas.MosaicToMosaicActorEnum
Model task types that produce raster prediction outputs from raster inputs.Values
str
Produce continuous numeric predictions for each output pixel.
str
Stack multiple time steps as model inputs and produce one semantic-segmentation output for change detection.
str
Produce per-pixel class probabilities with a semantic-segmentation model.
str
Produce embedding bands from time-stamped imagery with a temporal embedding model.
ResamplingMethod
Methods for calculating output pixels when RasterFlow resizes imagery.Values
str
Compute the weighted average of contributing pixels that contain data.
str
Interpolate from nearby source pixels with a bilinear kernel.
str
Interpolate from nearby source pixels with a cubic convolution kernel.
str
Interpolate from nearby source pixels with a cubic B-spline kernel.
str
Apply a Gaussian kernel when downsampling imagery.
str
Interpolate from nearby source pixels with a Lanczos windowed-sinc kernel.
str
Select the nearest source pixel. This is the fastest option and preserves categorical values.
str
Compute the root mean square of contributing pixels that contain data.
SemSegRasterioConfig
__init__ [Signature][inspect.Signature] of the model.
pydantic_complete: Whether model building is completed, or if there are still undefined fields. pydantic_core_schema: The core schema of the model. pydantic_custom_init: Whether the model has a custom __init__ function. pydantic_decorators: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1. pydantic_generic_metadata: Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these. pydantic_parent_namespace: Parent namespace of the model, used for automatic rebuilding of models. pydantic_post_init: The name of the post-init method for the model, if defined. pydantic_root_model: Whether the model is a [RootModel][pydantic.root_model.RootModel]. pydantic_serializer: The pydantic-core SchemaSerializer used to dump instances of the model. pydantic_validator: The pydantic-core SchemaValidator used to validate instances of the model.
pydantic_fields: A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. pydantic_computed_fields: A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
pydantic_extra: A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'. pydantic_fields_set: The names of fields explicitly set during instantiation. pydantic_private: Values of private attributes set on the model instance.
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
TemporalScoreMethodEnum
Reference methods for scoring how each time step differs from a time series.Values
str
Compare each time step with the immediately preceding time step.
str
Compare each time step with the mean of all other time steps.
str
Compare each time step with the medoid of all other time steps.
UriOutput
Attributes
any
URL to view this artifact in the Wherobots Cloud map viewer.
VectorizeMethodEnum
Methods for converting raster prediction bands to vector geometries.Values
str
Threshold each semantic-segmentation score band, group connected foreground pixels, and convert those groups to polygon geometries.