Merge pull request #271 from bioimage-io/update-pred

Updates to prediction functionality etc

bioimageio/core/VERSION

@@ -1,3 +1,3 @@
 {
-    "version": "0.5.3post2"
+    "version": "0.5.4"
 }

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/prediction.py

@@ -183,7 +183,7 @@ 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.
@@ -305,7 +305,7 @@ 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

@@ -60,7 +60,7 @@ 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
@@ -81,7 +81,7 @@ 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):
@@ -129,7 +129,7 @@ def test_resource(
                 assert len(inputs) == len(model.inputs)  # should be checked by validation
                 input_shapes = {}
                 for idx, (ipt, ipt_spec) in enumerate(zip(inputs, model.inputs)):
-                    if not _validate_input_shape(tuple(ipt.shape), ipt_spec.shape):
+                    if not check_input_shape(tuple(ipt.shape), ipt_spec.shape):
                         raise ValidationError(
                             f"Shape {tuple(ipt.shape)} of test input {idx} '{ipt_spec.name}' does not match "
                             f"input shape description: {ipt_spec.shape}."
@@ -138,7 +138,7 @@ def test_resource(
 
                 assert len(expected) == len(model.outputs)  # should be checked by validation
                 for idx, (out, out_spec) in enumerate(zip(expected, model.outputs)):
-                    if not _validate_output_shape(tuple(out.shape), out_spec.shape, input_shapes):
+                    if not check_output_shape(tuple(out.shape), out_spec.shape, input_shapes):
                         error = (error or "") + (
                             f"Shape {tuple(out.shape)} of test output {idx} '{out_spec.name}' does not match "
                             f"output shape description: {out_spec.shape}."