Merge branch 'main' into extend_test_resources

# Conflicts:
#	bioimageio/core/resource_tests.py

Author: FynnBe

bioimageio/core/VERSION

@@ -1,3 +1,3 @@
 {
-    "version": "0.5.3post2"
+    "version": "0.5.5"
 }

bioimageio/core/__init__.py

@@ -11,4 +11,5 @@
     serialize_raw_resource_description,
 )
 from .prediction_pipeline import create_prediction_pipeline
-from .prediction import predict_image, predict_images
+from .prediction import predict_image, predict_images, predict_with_padding, predict_with_tiling
+from .resource_tests import check_input_shape, check_output_shape, test_resource

bioimageio/core/build_spec/build_model.py

@@ -2,12 +2,13 @@
 import hashlib
 import os
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Union
 from warnings import warn
 
 import imageio
 import numpy as np
 import requests
+import tifffile
 
 import bioimageio.spec as spec
 import bioimageio.spec.model as model_spec
@@ -21,12 +22,6 @@
 except ImportError:
     from typing_extensions import get_args  # type: ignore
 
-# need tifffile for writing the deepimagej config
-# we probably always have this, but wrap into an ImportGuard just in case
-try:
-    import tifffile
-except ImportError:
-    tifffile = None
 
 #
 # utility functions to build the spec from python
@@ -419,35 +414,40 @@ def get_size(fname, axes):
 
 def _write_sample_data(input_paths, output_paths, input_axes, output_axes, pixel_sizes, export_folder: Path):
     def write_im(path, im, axes, pixel_size=None):
-        assert tifffile is not None, "need tifffile for writing deepimagej config"
         assert len(axes) == im.ndim, f"{len(axes), {im.ndim}}"
         assert im.ndim in (4, 5), f"{im.ndim}"
 
         # convert the image to expects (Z)CYX axis order
         if im.ndim == 4:
             assert set(axes) == {"b", "x", "y", "c"}, f"{axes}"
-            axes_ij = "cyxb"
+            resolution_axes_ij = "cyxb"
         else:
             assert set(axes) == {"b", "x", "y", "z", "c"}, f"{axes}"
-            axes_ij = "zcyxb"
+            resolution_axes_ij = "bzcyx"
+
+        def addMissingAxes(im_axes):
+            needed_axes = ["b", "c", "x", "y", "z", "s"]
+            for ax in needed_axes:
+                if ax not in im_axes:
+                    im_axes += ax
+            return im_axes
+
+        axes_ij = "bzcyxs"
+        # Expand the image to ImageJ dimensions
+        im = np.expand_dims(im, axis=tuple(range(len(axes), len(axes_ij))))
 
-        axis_permutation = tuple(axes.index(ax) for ax in axes_ij)
+        axis_permutation = tuple(addMissingAxes(axes).index(ax) for ax in axes_ij)
         im = im.transpose(axis_permutation)
-        # expand to TZCYXS
-        if len(axes_ij) == 4:  # add singleton t and z axis
-            im = im[None, None]
-        else:  # add singeton z axis
-            im = im[None]
 
         if pixel_size is None:
             resolution = None
         else:
-            spatial_axes = list(set(axes_ij) - set("bc"))
-            resolution = tuple(1.0 / pixel_size[ax] for ax in axes_ij if ax in spatial_axes)
+            spatial_axes = list(set(resolution_axes_ij) - set("bc"))
+            resolution = tuple(1.0 / pixel_size[ax] for ax in resolution_axes_ij if ax in spatial_axes)
         # does not work for double
         if np.dtype(im.dtype) == np.dtype("float64"):
             im = im.astype("float32")
-        tifffile.imsave(path, im, imagej=True, resolution=resolution)
+        tifffile.imwrite(path, im, imagej=True, resolution=resolution)
 
     sample_in_paths = []
     for i, (in_path, axes) in enumerate(zip(input_paths, input_axes)):

bioimageio/core/prediction.py

@@ -186,7 +186,7 @@ def check_padding(padding):
 def predict_with_padding(
     prediction_pipeline: PredictionPipeline,
     inputs: Union[xr.DataArray, List[xr.DataArray], Tuple[xr.DataArray]],
-    padding: Union[bool, Dict[str, int]],
+    padding: Union[bool, Dict[str, int]] = True,
     pad_right: bool = True,
 ) -> List[xr.DataArray]:
     """Run prediction with padding for a single set of input(s) with a bioimage.io model.
@@ -308,7 +308,7 @@ def check_tiling(tiling):
 def predict_with_tiling(
     prediction_pipeline: PredictionPipeline,
     inputs: Union[xr.DataArray, List[xr.DataArray], Tuple[xr.DataArray]],
-    tiling: Union[bool, Dict[str, Dict[str, int]]],
+    tiling: Union[bool, Dict[str, Dict[str, int]]] = True,
     verbose: bool = False,
 ) -> List[xr.DataArray]:
     """Run prediction with tiling for a single set of input(s) with a bioimage.io model.

bioimageio/core/resource_tests.py

@@ -41,7 +41,7 @@ def test_model(
     )
 
 
-def _validate_input_shape(shape: Tuple[int, ...], shape_spec) -> bool:
+def check_input_shape(shape: Tuple[int, ...], shape_spec) -> bool:
     if isinstance(shape_spec, list):
         if shape != tuple(shape_spec):
             return False
@@ -62,7 +62,7 @@ def _validate_input_shape(shape: Tuple[int, ...], shape_spec) -> bool:
     return True
 
 
-def _validate_output_shape(shape: Tuple[int, ...], shape_spec, input_shapes) -> bool:
+def check_output_shape(shape: Tuple[int, ...], shape_spec, input_shapes) -> bool:
     if isinstance(shape_spec, list):
         return shape == tuple(shape_spec)
     elif isinstance(shape_spec, ImplicitOutputShape):

setup.py

@@ -32,7 +32,7 @@
         "ruamel.yaml",
         "tqdm",
         "xarray",
-        "tifffile<=2022.4.8",  # fixes Syntax error; see https://github.com/bioimage-io/core-bioimage-io-python/pull/259
+        "tifffile"
     ],
     include_package_data=True,
     extras_require={