Merge pull request #273 from Dana-Farber-AIOS/dev

v2.0.3

Author: ryanccarelli

pathml/core/slide_backends.py

@@ -250,9 +250,11 @@ class BioFormatsBackend(SlideBackend):
 
     Args:
         filename (str): path to image file on disk
+        dtype (numpy.dtype): data type of image. If ``None``, will use BioFormats to infer the data type from the
+            image's OME metadata. Defaults to ``None``.
     """
 
-    def __init__(self, filename):
+    def __init__(self, filename, dtype=None):
         self.filename = filename
         # init java virtual machine
         javabridge.start_vm(class_path=bioformats.JARS, max_heap_size="50G")
@@ -287,6 +289,37 @@ def __init__(self, filename):
         self.shape_list = sizeSeries  # shape on all levels
         self.metadata = bioformats.get_omexml_metadata(self.filename)
 
+        if dtype:
+            assert isinstance(
+                dtype, np.dtype
+            ), f"dtype is of type {type(dtype)}. Must be a np.dtype"
+            self.pixel_dtype = dtype
+        else:
+            # infer pixel data type from metadata
+            # map from ome pixel datatypes to numpy types. Based on:
+            # https://github.com/CellProfiler/python-bioformats/blob/c03fb0988caf686251707adc4332d0aff9f02941/bioformats/omexml.py#L77-L87
+            # but specifying that float = float32 (np.float defaults to float64)
+            pixel_dtype_map = {
+                bioformats.omexml.PT_INT8: np.dtype("int8"),
+                bioformats.omexml.PT_INT16: np.dtype("int16"),
+                bioformats.omexml.PT_INT32: np.dtype("int32"),
+                bioformats.omexml.PT_UINT8: np.dtype("uint8"),
+                bioformats.omexml.PT_UINT16: np.dtype("uint16"),
+                bioformats.omexml.PT_UINT32: np.dtype("uint32"),
+                bioformats.omexml.PT_FLOAT: np.dtype("float32"),
+                bioformats.omexml.PT_BIT: np.dtype("bool"),
+                bioformats.omexml.PT_DOUBLE: np.dtype("float64"),
+            }
+            ome_pixeltype = (
+                bioformats.OMEXML(self.metadata).image().Pixels.get_PixelType()
+            )
+            try:
+                self.pixel_dtype = pixel_dtype_map[ome_pixeltype]
+            except:
+                raise Exception(
+                    f"pixel type '{ome_pixeltype}' detected from OME metadata not recognized."
+                )
+
     def __repr__(self):
         return f"BioFormatsBackend('{self.filename}')"
 
@@ -423,8 +456,12 @@ def extract_region(self, location, size, level=0, series_as_channels=False):
                         else:
                             array[:, :, z, level, t] = slicearray
 
-        array = array.astype(np.uint8)
-        return array
+        # scale array before converting: https://github.com/Dana-Farber-AIOS/pathml/issues/271
+        # first scale to [0-1]
+        array_scaled = array / (2 ** (8 * self.pixel_dtype.itemsize))
+        # then scale to [0-255] and convert to 8 bit
+        array_scaled = array_scaled * 2 ** 8
+        return array_scaled.astype(np.uint8)
 
     def get_thumbnail(self, size=None):
         """