Add support for floating point TIFF files in verification of image-based tool outputs

lib/galaxy/tool_util/verify/__init__.py

@@ -32,6 +32,10 @@
     from PIL import Image
 except ImportError:
     pass
+try:
+    import tifffile
+except ImportError:
+    pass
 
 from galaxy.tool_util.parser.util import (
     DEFAULT_DELTA,
@@ -496,14 +500,29 @@ def get_image_metric(
         raise ValueError(f'No such metric: "{metric_name}"')
 
 
+def _load_image(filepath: str) -> "numpy.typing.NDArray":
+    """
+    Reads the given image, trying tifffile and Pillow for reading.
+    """
+    # Try reading with tifffile first. It fails if the file is not a TIFF.
+    try:
+        arr = tifffile.imread(filepath)
+
+    # If tifffile failed, then the file is not a tifffile. In that case, try with Pillow.
+    except tifffile.TiffFileError:
+        with Image.open(filepath) as im:
+            arr = numpy.array(im)
+
+    # Return loaded image
+    return arr
+
+
 def files_image_diff(file1: str, file2: str, attributes: Optional[Dict[str, Any]] = None) -> None:
     """Check the pixel data of 2 image files for differences."""
     attributes = attributes or {}
 
-    with Image.open(file1) as im1:
-        arr1 = numpy.array(im1)
-    with Image.open(file2) as im2:
-        arr2 = numpy.array(im2)
+    arr1 = _load_image(file1)
+    arr2 = _load_image(file2)
 
     if arr1.dtype != arr2.dtype:
         raise AssertionError(f"Image data types did not match ({arr1.dtype}, {arr2.dtype}).")

lib/galaxy/tool_util/verify/asserts/image.py

@@ -18,6 +18,10 @@
     from PIL import Image
 except ImportError:
     pass
+try:
+    import tifffile
+except ImportError:
+    pass
 
 if TYPE_CHECKING:
     import numpy.typing
@@ -58,18 +62,17 @@ def assert_has_image_width(
     """
     Asserts the specified output is an image and has a width of the specified value.
     """
-    buf = io.BytesIO(output_bytes)
-    with Image.open(buf) as im:
-        _assert_number(
-            im.size[0],
-            width,
-            delta,
-            min,
-            max,
-            negate,
-            "{expected} width {n}+-{delta}",
-            "{expected} width to be in [{min}:{max}]",
-        )
+    im_arr = _get_image(output_bytes)
+    _assert_number(
+        im_arr.shape[1],
+        width,
+        delta,
+        min,
+        max,
+        negate,
+        "{expected} width {n}+-{delta}",
+        "{expected} width to be in [{min}:{max}]",
+    )
 
 
 def assert_has_image_height(
@@ -83,18 +86,17 @@ def assert_has_image_height(
     """
     Asserts the specified output is an image and has a height of the specified value.
     """
-    buf = io.BytesIO(output_bytes)
-    with Image.open(buf) as im:
-        _assert_number(
-            im.size[1],
-            height,
-            delta,
-            min,
-            max,
-            negate,
-            "{expected} height {n}+-{delta}",
-            "{expected} height to be in [{min}:{max}]",
-        )
+    im_arr = _get_image(output_bytes)
+    _assert_number(
+        im_arr.shape[0],
+        height,
+        delta,
+        min,
+        max,
+        negate,
+        "{expected} height {n}+-{delta}",
+        "{expected} height to be in [{min}:{max}]",
+    )
 
 
 def assert_has_image_channels(
@@ -108,18 +110,18 @@ def assert_has_image_channels(
     """
     Asserts the specified output is an image and has the specified number of channels.
     """
-    buf = io.BytesIO(output_bytes)
-    with Image.open(buf) as im:
-        _assert_number(
-            len(im.getbands()),
-            channels,
-            delta,
-            min,
-            max,
-            negate,
-            "{expected} image channels {n}+-{delta}",
-            "{expected} image channels to be in [{min}:{max}]",
-        )
+    im_arr = _get_image(output_bytes)
+    n_channels = 1 if im_arr.ndim < 3 else im_arr.shape[2]  # we assume here that the image is a 2-D image
+    _assert_number(
+        n_channels,
+        channels,
+        delta,
+        min,
+        max,
+        negate,
+        "{expected} image channels {n}+-{delta}",
+        "{expected} image channels to be in [{min}:{max}]",
+    )
 
 
 def _compute_center_of_mass(im_arr: "numpy.typing.NDArray") -> Tuple[float, float]:
@@ -139,10 +141,20 @@ def _get_image(
 ) -> "numpy.typing.NDArray":
     """
     Returns the output image or a specific channel.
+
+    The function tries to read the image using tifffile and Pillow.
     """
     buf = io.BytesIO(output_bytes)
-    with Image.open(buf) as im:
-        im_arr = numpy.array(im)
+
+    # Try reading with tifffile first. It fails if the file is not a TIFF.
+    try:
+        im_arr = tifffile.imread(buf)
+
+    # If tifffile failed, then the file is not a tifffile. In that case, try with Pillow.
+    except tifffile.TiffFileError:
+        buf.seek(0)
+        with Image.open(buf) as im:
+            im_arr = numpy.array(im)
 
     # Select the specified channel (if any).
     if channel is not None:

packages/tool_util/setup.cfg

@@ -70,6 +70,7 @@ extended-assertions =
     numpy
     pysam
     pillow
+    tifffile
 
 [options.packages.find]
 exclude =

test/functional/tools/image_diff.xml

@@ -22,6 +22,11 @@
       <param name="in" value="im1_uint8.png" />
       <output name="out" value="im1_uint8.png" compare="image_diff" metric="rms" eps="0" />
     </test>
+    <!-- test pair of equal images (float tiff) -->
+    <test>
+      <param name="in" value="im4_float.tif" />
+      <output name="out" value="im4_float.tif" compare="image_diff" />
+    </test>
     <!-- test pair of different images -->
     <test>
       <param name="in" value="im2_a.png" />

test/functional/tools/validation_image.xml

@@ -93,6 +93,18 @@
                 </assert_contents>
             </output>
         </test>
+        <!-- Tests with float TIFF images -->
+        <test>
+            <param name="input" value="im4_float.tif" />
+            <output name="output">
+                <assert_contents>
+                    <has_image_width width="25" />
+                    <has_image_height height="25" />
+                    <has_image_channels channels="1" />
+                    <has_image_center_of_mass center_of_mass="11.75, 11.75" />
+                </assert_contents>
+            </output>
+        </test>
         <!-- Tests with label images -->
         <test>
             <param name="input" value="im2_b.png" />