Fix ingestion of segmentation masks

ingestion_tools/scripts/common/image.py

@@ -71,7 +71,7 @@ def pyramid_to_mrc(
         mrcfiles.append(os.path.basename(filename))
 
         if write:
-            newfile = mrcfile.new(filename, self.data, overwrite=True)
+            newfile = mrcfile.new(filename, pyramid[0], overwrite=True)
             self.update_headers(newfile, header_mapper, voxel_spacing)
             newfile.flush()
             newfile.close()

ingestion_tools/scripts/importers/annotation.py

@@ -85,12 +85,12 @@ def __init__(
         glob_string: str,
         glob_vars: dict[str, str],
         file_format: str,
-        is_viz_default: bool = False,
+        is_visualization_default: bool = False,
     ):
         self.glob_string = glob_string.format(**glob_vars)
         self.file_format = file_format
         self.shape = shape
-        self.is_viz_default = is_viz_default
+        self.is_viz_default = is_visualization_default
         if self.file_format not in ["mrc"]:
             raise NotImplementedError("We only support MRC files for segmentation masks")
 
@@ -107,13 +107,13 @@ def __init__(
         glob_vars: dict[str, str],
         file_format: str,
         mask_label: int = 1,  # No explicit label means we are dealing with a binary mask already
-        is_viz_default: bool = False,
+        is_visualization_default: bool = False,
     ):
         self.glob_string = glob_string.format(**glob_vars)
         self.file_format = file_format
         self.shape = "SegmentationMask"  # Don't expose SemanticSegmentationMask to the public portal.
         self.label = mask_label
-        self.is_viz_default = is_viz_default
+        self.is_viz_default = is_visualization_default
 
         if self.file_format not in ["mrc"]:
             raise NotImplementedError("We only support MRC files for segmentation masks")
@@ -138,15 +138,15 @@ def __init__(
         glob_vars: dict[str, str],
         file_format: str,
         columns: str,
-        is_viz_default: bool = False,
+        is_visualization_default: bool = False,
         delimiter: str = ",",
     ):
         self.glob_string = glob_string.format(**glob_vars)
         self.file_format = file_format
         self.columns = columns
         self.shape = shape
         self.delimiter = delimiter
-        self.is_viz_default = is_viz_default
+        self.is_viz_default = is_visualization_default
         if self.file_format not in ["csv", "csv_with_header"]:
             raise NotImplementedError("We only support CSV files for Point files")
 
@@ -170,16 +170,16 @@ def load(
         annotation_set = []
         with fs.open(csvfilename, "r") as data:
             points = csv.reader(data, delimiter=self.delimiter)
-        if skip_header:
-            next(points)
-        for coord in points:
-            annotation_set.append(
-                self.point(
-                    float(coord[coord_order[0]]),
-                    float(coord[coord_order[1]]),
-                    float(coord[coord_order[2]]),
-                ),
-            )
+            if skip_header:
+                next(points)
+            for coord in points:
+                annotation_set.append(
+                    self.point(
+                        float(coord[coord_order[0]]),
+                        float(coord[coord_order[1]]),
+                        float(coord[coord_order[2]]),
+                    ),
+                )
         return annotation_set
 
     def get_metadata(self, output_prefix: str):
@@ -227,7 +227,7 @@ def __init__(
         file_format: str,
         binning: int,
         glob_string: str,
-        is_viz_default: bool = False,
+        is_visualization_default: bool = False,
         order: str | None = None,
         filter_value: str | None = None,
     ):
@@ -239,7 +239,7 @@ def __init__(
         self.glob_string = glob_string.format(**glob_vars)
         self.order = order
         self.filter_value = ""
-        self.is_viz_default = is_viz_default
+        self.is_viz_default = is_visualization_default
         if filter_value:
             self.filter_value = filter_value.format(**glob_vars)
         valid_formats = self.map_functions.keys()