Use tifffile to read compressed tif files

test/util/test_imageio.py

@@ -0,0 +1,27 @@
+import os
+import tempfile
+import unittest
+
+import numpy as np
+import tifffile
+
+
+class TestImageRead(unittest.TestCase):
+    def test_read_memap(self):
+        from torch_em.util.image import load_image, supports_memmap
+
+        with tempfile.TemporaryDirectory() as td:
+            tifffile.imwrite(os.path.join(td, "test.tif"), np.zeros((10, 10, 2)))
+            self.assert_(supports_memmap(os.path.join(td, "test.tif")))
+            data = load_image(os.path.join(td, "test.tif"))
+            self.assertEqual(data.shape, (10, 10, 2))
+
+    def test_read_copressed(self):
+        from torch_em.util.image import load_image
+
+        with tempfile.TemporaryDirectory() as td:
+            tifffile.imwrite(os.path.join(td, "test.tif"), np.zeros((10, 10, 2)), compression="ADOBE_DEFLATE")
+            data = load_image(os.path.join(td, "test.tif"))
+            self.assertEqual(data.shape, (10, 10, 2))
+
+

torch_em/util/image.py

@@ -1,7 +1,7 @@
 # TODO this should be partially refactored into elf.io before the next elf release
 # and then be used in image_stack_wrapper as welll
 import os
-import imageio
+import imageio.v2 as imageio
 
 try:
     import tifffile
@@ -27,6 +27,8 @@ def supports_memmap(image_path):
 def load_image(image_path):
     if supports_memmap(image_path):
         return tifffile.memmap(image_path, mode='r')
+    elif tifffile is not None and os.path.splitext(image_path)[1].lower() in {".tiff", ".tif"}:
+        return tifffile.imread(image_path)
     else:
         # TODO handle multi-channel images
         return imageio.imread(image_path)