Merge pull request #194 from siapy/fix

Fix

Author: janezlapajne

scripts/install-dev.sh

@@ -11,4 +11,4 @@ pdm install
 
 # Install pre-commit
 pdm run pre-commit uninstall
-pdm run pre-commit install --hook-type commit-msg
+pdm run pre-commit install # --hook-type commit-msg

siapy/entities/__init__.py

@@ -1,15 +1,13 @@
 from .images import SpectralImage
 from .imagesets import SpectralImageSet
 from .pixels import Pixels
-from .shapefiles import Shapefile
-from .shapes import Shape
+from .shapes import Shapefile
 from .signatures import Signatures
 
 __all__ = [
     "SpectralImage",
     "SpectralImageSet",
     "Pixels",
     "Signatures",
-    "Shape",
     "Shapefile",
 ]

siapy/entities/images/interfaces.py

@@ -1,10 +1,13 @@
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Any
+from typing import TYPE_CHECKING, Any
 
 import numpy as np
 from PIL import Image
 
+if TYPE_CHECKING:
+    from siapy.core.types import XarrayType
+
 __all__ = [
     "ImageBase",
 ]
@@ -58,3 +61,7 @@ def to_display(self, equalize: bool = True) -> Image.Image:
     @abstractmethod
     def to_numpy(self, nan_value: float | None = None) -> np.ndarray:
         pass
+
+    @abstractmethod
+    def to_xarray(self) -> "XarrayType":
+        pass

siapy/entities/images/rasterio_lib.py

@@ -35,7 +35,7 @@ def open(cls, filepath: str | Path) -> "RasterioLibImage":
             raise InvalidInputError({"filepath": str(filepath)}, f"Failed to open raster file: {e}") from e
 
         if isinstance(raster, list):
-            raise InvalidInputError({"file_type": type(raster).__name__}, "Expected DataArray, got Dataset")
+            raise InvalidInputError({"file_type": type(raster).__name__}, "Expected DataArray or Dataset, got list")
 
         return cls(raster)
 
@@ -49,44 +49,41 @@ def filepath(self) -> Path:
 
     @property
     def metadata(self) -> dict[str, Any]:
-        return dict(self.file.attrs)
+        return self.file.attrs
 
     @property
     def shape(self) -> tuple[int, int, int]:
         # rioxarray uses (band, y, x) ordering
         return (self.file.y.size, self.file.x.size, self.file.band.size)
 
+    @property
+    def rows(self) -> int:
+        return self.file.y.size
+
+    @property
+    def cols(self) -> int:
+        return self.file.x.size
+
     @property
     def bands(self) -> int:
         return self.file.band.size
 
     @property
     def default_bands(self) -> list[int]:
         # Most common RGB band combination for satellite imagery
-        if self.bands >= 3:
-            return [0, 1, 2]
-        return list(range(min(3, self.bands)))
+        return list(range(1, min(3, self.bands) + 1))
 
     @property
     def wavelengths(self) -> list[float]:
-        # Try to get wavelengths from band attributes
-        wavelengths = []
-        for band_idx in range(self.bands):
-            band_data = self.file.sel(band=band_idx + 1)
-            wave = band_data.attrs.get("wavelength")
-            if wave:
-                wavelengths.append(float(wave))
-            else:
-                wavelengths.append(float(band_idx + 1))
-        return wavelengths
+        return self.file.band.values
 
     @property
     def camera_id(self) -> str:
+        # Todo: camera_id is not a standard metadata field, should be updated
         return self.metadata.get("camera_id", "")
 
     def to_display(self, equalize: bool = True) -> Image.Image:
-        selected_bands = [i + 1 for i in self.default_bands]  # Adjust for 1-indexed bands
-        bands_data = self.file.sel(band=selected_bands)
+        bands_data = self.file.sel(band=self.default_bands)
         image_3ch = bands_data.transpose("y", "x", "band").values
         image_3ch_clean = np.nan_to_num(np.asarray(image_3ch))
         min_val = np.nanmin(image_3ch_clean)
@@ -100,7 +97,10 @@ def to_display(self, equalize: bool = True) -> Image.Image:
         return image
 
     def to_numpy(self, nan_value: float | None = None) -> np.ndarray:
-        image = np.moveaxis(np.asarray(self.file.values), 0, -1)
+        image = np.asarray(self.file.transpose("y", "x", "band").values)
         if nan_value is not None:
             image = np.nan_to_num(image, nan=nan_value)
         return image
+
+    def to_xarray(self) -> "XarrayType":
+        return self.file

siapy/entities/images/spectral_lib.py

@@ -5,14 +5,15 @@
 
 import numpy as np
 import spectral as sp
+import xarray as xr
 from PIL import Image, ImageOps
 
 from siapy.core.exceptions import InvalidFilepathError, InvalidInputError
 
 from .interfaces import ImageBase
 
 if TYPE_CHECKING:
-    from siapy.core.types import SpectralLibType
+    from siapy.core.types import SpectralLibType, XarrayType
 
 __all__ = [
     "SpectralLibImage",
@@ -117,6 +118,20 @@ def _remove_nan(self, image: np.ndarray, nan_value: float = 0.0) -> np.ndarray:
         image[~image_mask] = nan_value
         return image
 
+    def to_xarray(self) -> "XarrayType":
+        data = self._file[:, :, :]
+        xarray = xr.DataArray(
+            data,
+            dims=["y", "x", "band"],
+            coords={
+                "y": np.arange(self.rows),
+                "x": np.arange(self.cols),
+                "band": self.wavelengths,
+            },
+            attrs=self._file.metadata,
+        )
+        return xarray
+
 
 def _parse_description(description: str) -> dict[str, Any]:
     def _parse():

siapy/entities/images/spimage.py

@@ -5,12 +5,15 @@
 import numpy as np
 from PIL import Image
 
-from ..shapes import GeometricShapes, Shape
+from ..shapes import GeometricShapes, ShapeBase
 from ..signatures import Signatures
 from .interfaces import ImageBase
+from .rasterio_lib import RasterioLibImage
 from .spectral_lib import SpectralLibImage
 
 if TYPE_CHECKING:
+    from siapy.core.types import XarrayType
+
     from ..pixels import Pixels
 
 
@@ -26,7 +29,7 @@ class SpectralImage(Generic[T]):
     def __init__(
         self,
         image: T,
-        geometric_shapes: list["Shape"] | None = None,
+        geometric_shapes: list["ShapeBase"] | None = None,
     ):
         self._image = image
         self._geometric_shapes = GeometricShapes(self, geometric_shapes)
@@ -52,10 +55,10 @@ def spy_open(
         image = SpectralLibImage.open(header_path=header_path, image_path=image_path)
         return SpectralImage(image)
 
-    # @classmethod
-    # def rasterio_open(cls, filepath: str | Path) -> "SpectralImage":
-    #     image = RasterioLib.open(filepath)
-    #     return cls(image)
+    @classmethod
+    def rasterio_open(cls, filepath: str | Path) -> "SpectralImage[RasterioLibImage]":
+        image = RasterioLibImage.open(filepath)
+        return SpectralImage(image)
 
     @property
     def image(self) -> T:
@@ -99,6 +102,9 @@ def to_display(self, equalize: bool = True) -> Image.Image:
     def to_numpy(self, nan_value: float | None = None) -> np.ndarray:
         return self.image.to_numpy(nan_value)
 
+    def to_xarray(self) -> "XarrayType":
+        return self.image.to_xarray()
+
     def to_signatures(self, pixels: "Pixels") -> Signatures:
         image_arr = self.to_numpy()
         signatures = Signatures.from_array_and_pixels(image_arr, pixels)