Compute RasterStats from transformed RasterSource

rastervision_core/rastervision/core/__init__.py

@@ -2,7 +2,7 @@
 
 
 def register_plugin(registry):
-    registry.set_plugin_version('rastervision.core', 13)
+    registry.set_plugin_version('rastervision.core', 14)
     from rastervision.core.cli import predict, predict_scene
     registry.add_plugin_command(predict)
     registry.add_plugin_command(predict_scene)

rastervision_core/rastervision/core/data/raster_source/multi_raster_source.py

@@ -278,6 +278,6 @@ def get_chip(self, window: Box,
         chip = chip[..., self.channel_order]
 
         for transformer in self.raster_transformers:
-            chip = transformer.transform(chip, self.channel_order)
+            chip = transformer.transform(chip)
 
         return chip

rastervision_core/rastervision/core/data/raster_source/multi_raster_source_config.py

@@ -64,7 +64,10 @@ def validate_temporal(self) -> Self:
     def build(self, tmp_dir: str | None = None,
               use_transformers: bool = True) -> MultiRasterSource:
         if use_transformers:
-            raster_transformers = [t.build() for t in self.transformers]
+            raster_transformers = [
+                t.build(channel_order=self.channel_order)
+                for t in self.transformers
+            ]
         else:
             raster_transformers = []
 

rastervision_core/rastervision/core/data/raster_source/raster_source.py

@@ -142,7 +142,7 @@ def get_chip(self, window: 'Box',
         chip = chip[..., self.channel_order]
 
         for transformer in self.raster_transformers:
-            chip = transformer.transform(chip, self.channel_order)
+            chip = transformer.transform(chip)
 
         return chip
 

rastervision_core/rastervision/core/data/raster_source/rasterio_source.py

@@ -198,7 +198,7 @@ def get_chip(self,
             bands = self.bands_to_read[bands]
         chip = self._get_chip(window, out_shape=out_shape, bands=bands)
         for transformer in self.raster_transformers:
-            chip = transformer.transform(chip, self.channel_order)
+            chip = transformer.transform(chip)
         return chip
 
     def __getitem__(self, key: Any) -> 'np.ndarray':

rastervision_core/rastervision/core/data/raster_source/rasterio_source_config.py

@@ -34,9 +34,15 @@ class RasterioSourceConfig(RasterSourceConfig):
         False,
         description='Stream assets as needed rather than downloading them.')
 
-    def build(self, tmp_dir, use_transformers=True):
-        raster_transformers = ([rt.build() for rt in self.transformers]
-                               if use_transformers else [])
+    def build(self, tmp_dir: str | None,
+              use_transformers: bool = True) -> RasterioSource:
+        if use_transformers:
+            raster_transformers = [
+                t.build(channel_order=self.channel_order)
+                for t in self.transformers
+            ]
+        else:
+            raster_transformers = []
         bbox = Box(*self.bbox) if self.bbox is not None else None
         return RasterioSource(
             uris=self.uris,

rastervision_core/rastervision/core/data/raster_source/temporal_multi_raster_source.py

@@ -115,7 +115,7 @@ def get_chip(self, window: Box,
         chip = np.stack(sub_chips)
 
         for transformer in self.raster_transformers:
-            chip = transformer.transform(chip, self.channel_order)
+            chip = transformer.transform(chip)
 
         return chip
 

rastervision_core/rastervision/core/data/raster_source/xarray_source.py

@@ -263,7 +263,7 @@ def get_chip(self,
         chip = self._get_chip(
             window, bands=bands, time=time, out_shape=out_shape)
         for transformer in self.raster_transformers:
-            chip = transformer.transform(chip, bands)
+            chip = transformer.transform(chip)
         return chip
 
     def __getitem__(self, key: Any) -> 'np.ndarray':

rastervision_core/rastervision/core/data/raster_source/xarray_source_config.py

@@ -36,8 +36,13 @@ class XarraySourceConfig(RasterSourceConfig):
     def build(self, tmp_dir: str | None = None,
               use_transformers: bool = True) -> XarraySource:
         item_or_item_collection = self.stac.build()
-        raster_transformers = ([rt.build() for rt in self.transformers]
-                               if use_transformers else [])
+        if use_transformers:
+            raster_transformers = [
+                t.build(channel_order=self.channel_order)
+                for t in self.transformers
+            ]
+        else:
+            raster_transformers = []
         raster_source = XarraySource.from_stac(
             item_or_item_collection,
             raster_transformers=raster_transformers,

rastervision_core/rastervision/core/data/raster_transformer/cast_transformer.py

@@ -19,14 +19,13 @@ def __init__(self, to_dtype: str):
     def __repr__(self):
         return repr_with_args(self, to_dtype=str(self.to_dtype))
 
-    def transform(self, chip: np.ndarray,
-                  channel_order: list | None = None) -> np.ndarray:
-        """Cast chip to self.to_dtype.
+    def transform(self, chip: np.ndarray) -> np.ndarray:
+        """Cast chip to dtype ``self.to_dtype``.
 
         Args:
-            chip: ndarray of shape [height, width, channels]
+            chip: Array of shape (..., H, W, C).
 
         Returns:
-            [height, width, channels] numpy array
+            Array of shape (..., H, W, C)
         """
         return chip.astype(self.to_dtype)

rastervision_core/rastervision/core/data/raster_transformer/cast_transformer_config.py

@@ -1,7 +1,7 @@
 from rastervision.pipeline.config import register_config, Field
 from rastervision.core.data.raster_transformer.raster_transformer_config import (  # noqa
     RasterTransformerConfig)
-from rastervision.core.data.raster_transformer.cast_transformer import (  # noqa
+from rastervision.core.data.raster_transformer.cast_transformer import (
     CastTransformer)
 
 
@@ -14,5 +14,5 @@ class CastTransformerConfig(RasterTransformerConfig):
         description='dtype to cast raster to. Must be a valid Numpy dtype '
         'e.g. "uint8", "float32", etc.')
 
-    def build(self):
+    def build(self, channel_order: list[int] | None = None):
         return CastTransformer(to_dtype=self.to_dtype)

rastervision_core/rastervision/core/data/raster_transformer/min_max_transformer.py

@@ -6,9 +6,7 @@
 class MinMaxTransformer(RasterTransformer):
     """Transforms chips by scaling values in each channel to span 0-255."""
 
-    def transform(self,
-                  chip: np.ndarray,
-                  channel_order: list[int] | None = None) -> np.ndarray:
+    def transform(self, chip: np.ndarray) -> np.ndarray:
         c = chip.shape[-1]
         pixels = chip.reshape(-1, c)
         channel_mins = pixels.min(axis=0)

rastervision_core/rastervision/core/data/raster_transformer/min_max_transformer_config.py

@@ -7,5 +7,5 @@
 class MinMaxTransformerConfig(RasterTransformerConfig):
     """Configure a :class:`.MinMaxTransformer`."""
 
-    def build(self):
+    def build(self, channel_order: list[int] | None = None):
         return MinMaxTransformer()

rastervision_core/rastervision/core/data/raster_transformer/nan_transformer.py

@@ -8,27 +8,22 @@ class NanTransformer(RasterTransformer):
     """Removes NaN values from float raster."""
 
     def __init__(self, to_value: float = 0.0):
-        """Construct a new NanTransformer.
+        """Constructor.
 
         Args:
-            to_value: (float) NaN values are replaced
-                with this
+            to_value: NaN values are replaced with this.
         """
         self.to_value = to_value
 
-    def transform(self, chip, channel_order=None):
-        """Transform a chip.
-
-        Removes NaN values.
+    def transform(self, chip):
+        """Removes NaN values.
 
         Args:
-            chip: ndarray of shape [height, width, channels] This is assumed to already
-                have the channel_order applied to it if channel_order is set. In other
-                words, channels should be equal to len(channel_order).
+            chip: Array of shape (..., H, W, C).
 
         Returns:
-            [height, width, channels] numpy array
-
+            Array of shape (..., H, W, C)
         """
-        chip[np.isnan(chip)] = self.to_value
+        nan_mask = np.isnan(chip)
+        chip[nan_mask] = self.to_value
         return chip

rastervision_core/rastervision/core/data/raster_transformer/nan_transformer_config.py

@@ -12,5 +12,5 @@ class NanTransformerConfig(RasterTransformerConfig):
     to_value: float | None = Field(
         0.0, description=('Turn all NaN values into this value.'))
 
-    def build(self):
+    def build(self, channel_order: list[int] | None = None):
         return NanTransformer(to_value=self.to_value)

rastervision_core/rastervision/core/data/raster_transformer/raster_transformer.py

@@ -9,17 +9,12 @@ class RasterTransformer(ABC):
     """Transforms raw chips to be input to a neural network."""
 
     @abstractmethod
-    def transform(self, chip: 'np.ndarray',
-                  channel_order=None) -> 'np.ndarray':
+    def transform(self, chip: 'np.ndarray') -> 'np.ndarray':
         """Transform a chip of a raster source.
 
         Args:
-            chip: ndarray of shape [height, width, channels] This is assumed to already
-                have the channel_order applied to it if channel_order is set. In other
-                words, channels should be equal to len(channel_order).
-            channel_order: list of indices of channels that were extracted from the
-                raw imagery.
+            chip: Array of shape (..., H, W, C).
 
         Returns:
-            (np.ndarray): Array of shape (..., H, W, C)
+            Array of shape (..., H, W, C)
         """

rastervision_core/rastervision/core/data/raster_transformer/raster_transformer_config.py

@@ -2,7 +2,7 @@
 from rastervision.pipeline.config import Config, register_config
 
 if TYPE_CHECKING:
-    from rastervision.core.data import SceneConfig
+    from rastervision.core.data import RasterTransformer, SceneConfig
     from rastervision.core.rv_pipeline import RVPipelineConfig
 
 
@@ -17,3 +17,7 @@ def update(self,
 
     def update_root(self, root_dir: str):
         pass
+
+    def build(self,
+              channel_order: list[int] | None = None) -> 'RasterTransformer':
+        raise NotImplementedError()

rastervision_core/rastervision/core/data/raster_transformer/reclass_transformer.py

@@ -9,30 +9,21 @@ class ReclassTransformer(RasterTransformer):
     """Maps class IDs in a label raster to other values."""
 
     def __init__(self, mapping: dict[int, int]):
-        """Construct a new ReclassTransformer.
+        """Constructor.
 
         Args:
-            mapping: (dict) Remapping dictionary
+            mapping: Remapping dictionary, value_from-->value_to.
         """
         self.mapping = mapping
 
-    def transform(self,
-                  chip: 'np.ndarray',
-                  channel_order: list[int] | None = None):
-        """Transform a chip.
-
-        Reclassify a label raster using the given mapping.
+    def transform(self, chip: 'np.ndarray'):
+        """Reclassify a label raster using the given mapping.
 
         Args:
-            chip: ndarray of shape [height, width, channels] This is assumed to already
-                have the channel_order applied to it if channel_order is set. In other
-                words, channels should be equal to len(channel_order).
-            channel_order: list of indices of channels that were extracted from the
-                raw imagery.
+            chip: Array of shape (..., H, W, C).
 
         Returns:
-            [height, width, channels] numpy array
-
+            Array of shape (..., H, W, C)
         """
         masks = []
         for (value_from, value_to) in self.mapping.items():

rastervision_core/rastervision/core/data/raster_transformer/reclass_transformer_config.py

@@ -10,5 +10,6 @@ class ReclassTransformerConfig(RasterTransformerConfig):
     mapping: dict[int, int] = Field(
         ..., description=('The reclassification mapping.'))
 
-    def build(self) -> ReclassTransformer:
+    def build(self,
+              channel_order: list[int] | None = None) -> ReclassTransformer:
         return ReclassTransformer(mapping=self.mapping)

rastervision_core/rastervision/core/data/raster_transformer/rgb_class_transformer.py

@@ -37,19 +37,14 @@ def __init__(self, class_config: 'ClassConfig'):
             ],
             dtype=np.uint8)
 
-    def transform(self,
-                  chip: np.ndarray,
-                  channel_order: list[int] | None = None) -> np.ndarray:
+    def transform(self, chip: np.ndarray) -> np.ndarray:
         """Transform RGB array to array of class IDs or vice versa.
 
         Args:
-            chip (np.ndarray): Numpy array of shape (H, W, 3).
-            channel_order (list[int] | None): List of indices of
-                channels that were extracted from the raw imagery.
-                Defaults to None.
+            chip: Numpy array of shape (H, W, 3).
 
         Returns:
-            np.ndarray: An array of class IDs.
+            An array of class IDs of shape (H, W, 1).
         """
         return self.rgb_to_class(chip)
 

rastervision_core/rastervision/core/data/raster_transformer/rgb_class_transformer_config.py

@@ -13,5 +13,6 @@ class RGBClassTransformerConfig(RasterTransformerConfig):
         description=('The class config defining the mapping between '
                      'classes and colors.'))
 
-    def build(self) -> RGBClassTransformer:
+    def build(self,
+              channel_order: list[int] | None = None) -> RGBClassTransformer:
         return RGBClassTransformer(class_config=self.class_config)