In illumination correction, do not use hardcoded image size (ref #114)

Author: tcompa

fractal/tasks/illumination_correction.py

@@ -137,10 +137,34 @@ def illumination_correction(
         if not newzarrurl.endswith("/"):
             newzarrurl += "/"
 
-    # Hard-coded values for the image size
-    # FIXME can we parse this from somewhere?
-    img_size_y = 2160
-    img_size_x = 2560
+    # Read FOV ROIs
+    FOV_ROI_table = ad.read_zarr(f"{zarrurl}tables/FOV_ROI_table")
+
+    # Read pixel sizes from zattrs file
+    pixel_sizes_zyx = extract_zyx_pixel_sizes_from_zattrs(zarrurl + ".zattrs")
+
+    # Create list of indices for 3D FOVs spanning the entire Z direction
+    list_indices = convert_ROI_table_to_indices(
+        FOV_ROI_table,
+        level=0,
+        coarsening_xy=coarsening_xy,
+        pixel_sizes_zyx=pixel_sizes_zyx,
+    )
+
+    # Extract image size from FOV-ROI indices
+    # Note: this works at level=0, where FOVs should all be of the exact same
+    #       size (in pixels)
+    ref_img_size = None
+    for indices in list_indices:
+        img_size = (indices[3] - indices[2], indices[5] - indices[4])
+        if ref_img_size is None:
+            ref_img_size = img_size
+        else:
+            if img_size != ref_img_size:
+                raise Exception(
+                    "ERROR: inconsistent image sizes in list_indices"
+                )
+    img_size_y, img_size_x = img_size[:]
 
     # Load paths of correction matrices
     with open(path_dict_corr, "r") as jsonfile:
@@ -193,20 +217,6 @@ def illumination_correction(
             f"Error in illumination_correction, chunks_x: {chunks_x}"
         )
 
-    # Read FOV ROIs
-    FOV_ROI_table = ad.read_zarr(f"{zarrurl}tables/FOV_ROI_table")
-
-    # Read pixel sizes from zattrs file
-    pixel_sizes_zyx = extract_zyx_pixel_sizes_from_zattrs(zarrurl + ".zattrs")
-
-    # Create list of indices for 3D FOVs spanning the entire Z direction
-    list_indices = convert_ROI_table_to_indices(
-        FOV_ROI_table,
-        level=0,
-        coarsening_xy=coarsening_xy,
-        pixel_sizes_zyx=pixel_sizes_zyx,
-    )
-
     # Create the final list of single-Z-layer FOVs
     list_indices = split_3D_indices_into_z_layers(list_indices)
 

fractal/tasks/lib_regions_of_interest.py

@@ -9,9 +9,7 @@
 import pandas as pd
 
 
-def prepare_FOV_ROI_table(
-    df: pd.DataFrame,
-) -> ad.AnnData:
+def prepare_FOV_ROI_table(df: pd.DataFrame) -> ad.AnnData:
 
     for mu in ["x", "y", "z"]: