@@ -379,7 +379,7 @@ def _get_bins(path_bins: Path) -> list[str]:
379379 affine = Affine (affine_matrix , input_axes = ("x" , "y" ), output_axes = ("x" , "y" ))
380380
381381 # determine the size of the transformed image
382- bounding_box = get_extent (image )
382+ bounding_box = get_extent (image , coordinate_system = dataset_id )
383383 x0 , x1 = bounding_box ["x" ]
384384 y0 , y1 = bounding_box ["y" ]
385385 x1 -= 1
@@ -410,7 +410,7 @@ def _get_bins(path_bins: Path) -> list[str]:
410410 numpy_data , ProjectiveTransform (projective_shift ).inverse , output_shape = transformed_shape , order = 1
411411 )
412412 warped = np .round (warped * 255 ).astype (np .uint8 )
413- warped = Image2DModel .parse (warped , dims = ("y" , "x" , "c" ), transformations = {"global" : affine }, rgb = True )
413+ warped = Image2DModel .parse (warped , dims = ("y" , "x" , "c" ), transformations = {dataset_id : affine }, rgb = True )
414414
415415 # we replace the cytassist image with the warped image
416416 images [dataset_id + "_cytassist_image" ] = warped
@@ -484,7 +484,13 @@ def _load_image(
484484 ), "When the image is not in RGB, the first dimension should be the number of channels."
485485
486486 image = DataArray (data , dims = ("c" , "y" , "x" ))
487- parsed = Image2DModel .parse (image , scale_factors = scale_factors , rgb = None , ** image_models_kwargs )
487+ parsed = Image2DModel .parse (
488+ image ,
489+ scale_factors = scale_factors ,
490+ rgb = None ,
491+ transformations = {dataset_id : Identity ()},
492+ ** image_models_kwargs ,
493+ )
488494 images [dataset_id + suffix ] = parsed
489495 else :
490496 warnings .warn (f"File { path } does not exist, skipping it." , UserWarning , stacklevel = 2 )
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