Merge pull request #309 from imagej/rgb-data-transfer

Enable RGB image transfer

src/napari_imagej/types/converters/images.py

@@ -10,7 +10,7 @@
 from jpype import JArray, JByte
 from napari.layers import Image
 from napari.utils.colormaps import Colormap
-from numpy import ones
+from numpy import ones, uint8
 from scyjava import Priority
 from xarray import DataArray
 
@@ -59,6 +59,16 @@ def _image_layer_to_dataset(image: Image, **kwargs) -> "jc.Dataset":
     :param image: a napari Image layer
     :return: a Dataset
     """
+    # Define dimension order if necessary
+    if "dim_order" not in kwargs:
+        # NB "dim_i"s will be overwritten later
+        dim_order = [f"dim_{i}" for i in range(len(image.data.shape))]
+        # if RGB, last dimension is Channel
+        if image.rgb:
+            dim_order[-1] = "Channel"
+
+        kwargs["dim_order"] = dim_order
+
     # Construct a dataset from the data
     dataset: "jc.Dataset" = nij.ij.py.to_dataset(image.data, **kwargs)
 
@@ -86,8 +96,16 @@ def _image_layer_to_dataset(image: Image, **kwargs) -> "jc.Dataset":
 
     # Add name
     dataset.setName(image.name)
-    # Add color table, if the image uses a custom colormap
-    if image.colormap.name != "gray":
+
+    # Set RGB
+    if (
+        image.rgb
+        and dataset.dimensionIndex(jc.Axes.CHANNEL) > -1
+        and image.dtype == uint8
+    ):
+        dataset.setRGBMerged(True)
+    # or add color table, if the image uses a custom colormap
+    elif image.colormap.name != "gray":
         color_table = _colormap_to_color_table(image.colormap)
         dataset.initializeColorTables(1)
         dataset.setColorTable(color_table, 0)

src/napari_imagej/widgets/widget_utils.py

@@ -168,13 +168,14 @@ def __init__(self, title: str, choices: List[Layer], required=True):
 class DimsComboBox(QFrame):
     """A QFrame used to map the axes of a Layer to dimension labels"""
 
+    # NB: Strings correspond to supported net.imagej.axis.Axes types
     dims = [
         [],
         ["X"],
         ["Y", "X"],
         ["Z", "Y", "X"],
-        ["T", "Y", "X", "C"],
-        ["T", "Z", "Y", "X", "C"],
+        ["Time", "Y", "X", "Channel"],
+        ["Time", "Z", "Y", "X", "Channel"],
     ]
 
     def __init__(self, combo_box: LayerComboBox):
@@ -199,7 +200,12 @@ def update(self, index: int):
         # Determine the selected layer
         selected = self.selection_box.combo.itemData(index)
         # Guess dimension labels for the selection
-        guess = self.dims[len(selected.data.shape)]
+        ndim = len(selected.data.shape)
+        if isinstance(selected, Image) and selected.rgb:
+            guess = list(self.dims[ndim - 1])
+            guess.append("Channel")
+        else:
+            guess = self.dims[ndim]
         # Create dimension selectors for each dimension of the selection.
         for i, g in enumerate(guess):
             self.layout().addWidget(
@@ -220,7 +226,8 @@ def provided_labels(self):
     class DimSelector(QWidget):
         """A QWidget providing potential labels for each dimension"""
 
-        choices = ["X", "Y", "Z", "T", "C", "Unspecified"]
+        # NB: Strings correspond to supported net.imagej.axis.Axes types
+        choices = ["X", "Y", "Z", "Time", "Channel", "Unspecified"]
 
         def __init__(self, title: str, guess: str):
             # Define widget layout

tests/widgets/test_menu.py

@@ -328,9 +328,10 @@ def test_advanced_data_transfer(
     assert not button.isEnabled()
 
     # Add an image to the viewer
-    sample_data = numpy.ones((100, 100, 3))
+    sample_data = numpy.ones((100, 100, 3), dtype=numpy.uint8)
     image: Image = Image(data=sample_data, name="test_to")
     current_viewer().add_layer(image)
+    assert image.rgb
     asserter(lambda: button.isEnabled())
 
     # Add some rois to the viewer
@@ -374,6 +375,8 @@ def check_active_display():
         dataset = ij.display().getActiveDisplay().getActiveView().getData()
         if not dataset.getName() == "test_to":
             return False
+        if not dataset.isRGBMerged():
+            return False
         rois = dataset.getProperties().get("rois")
         return rois is not None
 
@@ -447,7 +450,7 @@ def test_modification_in_imagej(asserter, qtbot, ij, gui_widget: NapariImageJMen
 
     # Add some data to the viewer
     sample_data = numpy.ones((100, 100, 3), dtype=numpy.uint8)
-    image: Image = Image(data=sample_data, name="test_to")
+    image: Image = Image(data=sample_data, name="test_to", rgb=False)
     current_viewer().add_layer(image)
 
     # Press the button, handle the Dialog