Added Dask converter for ome.tiff reader, other small improvements

CHANGELOG.md

@@ -1,3 +1,6 @@
+#### Version 0.6.2
+- Added Dask converter for ome.tiff reader
+
 #### Version 0.6.1
 - Rewritten code base supporting full multi-dimensional images
 - Improved (ome) zarr support

OmeSliCC/OmeSource.py

@@ -149,6 +149,9 @@ def _init_sizes(self):
 
         self.output_dimension_order = 'tczyx'
 
+    def as_dask(self):
+        raise NotImplementedError('Implement method in subclass')
+
     def get_mag(self) -> float:
         mag = self.source_mag
         # get effective mag at target pixel size
@@ -214,7 +217,7 @@ def get_thumbnail(self, target_size: tuple, precise: bool = False) -> np.ndarray
             thumbnail = self.render(image_resize(image, target_size))
         return thumbnail
 
-    def get_window_min_max(self, channeli):
+    def get_channel_window(self, channeli):
         min_quantile = 0.001
         max_quantile = 0.999
 
@@ -266,12 +269,13 @@ def render(self, image: np.ndarray, t: int = 0, z: int = 0, channels: list = [])
                     else:
                         channel_values = image[..., channeli]
                     if do_normalisation:
-                        window = self.get_window_min_max(channeli)
+                        window = self.get_channel_window(channeli)
                         channel_values = normalise_values(channel_values, window['min'], window['max'])
                     else:
                         channel_values = int2float_image(channel_values)
-                    if 'color' in channel and channel['color'] != '':
-                        rgba = channel['color']
+                    color = channel.get('color')
+                    if color:
+                        rgba = color
                     else:
                         rgba = [1, 1, 1, 1]
                     color = rgba[:3]
@@ -283,7 +287,7 @@ def render(self, image: np.ndarray, t: int = 0, z: int = 0, channels: list = [])
                     tot_alpha += alpha
             new_image = float2int_image(new_image / tot_alpha)
         elif do_normalisation:
-            window = self.get_window_min_max(0)
+            window = self.get_channel_window(0)
             new_image = float2int_image(normalise_values(image, window['min'], window['max']))
         else:
             new_image = image

OmeSliCC/OmeZarrSource.py

@@ -98,6 +98,9 @@ def _find_metadata(self):
         self.channels = channels
         self.source_mag = 0
 
+    def as_dask(self):
+        return self.levels
+
     def _asarray_level(self, level: int, x0: float = 0, y0: float = 0, x1: float = -1, y1: float = -1,
                        c: int = None, z: int = None, t: int = None) -> np.ndarray:
         if x1 < 0 or y1 < 0:

OmeSliCC/TiffSource.py

@@ -1,11 +1,12 @@
 # https://pypi.org/project/tifffile/
 
 
-import os
+from concurrent.futures import ThreadPoolExecutor
+import dask.array as da
 from enum import Enum
 import numpy as np
+import os
 from tifffile import TiffFile, TiffPage
-from concurrent.futures import ThreadPoolExecutor
 
 from OmeSliCC import XmlDict
 from OmeSliCC.OmeSource import OmeSource
@@ -51,6 +52,7 @@ def __init__(self,
             self.executor = ThreadPoolExecutor(max_workers)
 
         tiff = TiffFile(filename)
+        self.tiff = tiff
         self.first_page = tiff.pages.first
         if tiff.is_ome and tiff.ome_metadata is not None:
             xml_metadata = tiff.ome_metadata
@@ -176,6 +178,9 @@ def _find_metadata(self):
         self.source_mag = mag
         self.channels = channels
 
+    def as_dask(self):
+        return [da.from_zarr(self.tiff.aszarr(level=level)) for level in range(len(self.sizes))]
+
     def load(self, decompress: bool = False):
         self.fh.seek(0)
         self.data = self.fh.read()

OmeSliCC/ome_zarr_util.py

@@ -44,7 +44,7 @@ def create_channel_metadata(source):
         if 'color' in channel:
             channel['color'] = rgba_to_hexrgb(channel['color'])
         if 'window' not in channel:
-            channel['window'] = source.get_window_min_max(channeli)
+            channel['window'] = source.get_channel_window(channeli)
         channels.append(channel)
 
     metadata = {

environment.yml

@@ -14,6 +14,7 @@ dependencies:
  - scikit-learn
  - imagecodecs
  - numcodecs
+ - dask
  - tifffile
  - zarr
  - ome-zarr

environment_no_bioformats.yml

@@ -13,6 +13,7 @@ dependencies:
  - scikit-learn
  - imagecodecs
  - numcodecs
+ - dask
  - tifffile
  - zarr
  - ome-zarr

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "OmeSliCC"
-version = "0.6.1"
+version = "0.6.2"
 description = "Ome(ro) Slide Image Conversion and Compression pipeline"
 readme = "README.md"
 license = {file = "LICENSE.md"}