add numpy_load helper

Author: FynnBe

bioimageio/core/image_helper.py

@@ -9,10 +9,11 @@
 from numpy.typing import NDArray
 from xarray import DataArray
 
-from bioimageio.spec.model.v0_4 import InputTensor as InputTensor04
-from bioimageio.spec.model.v0_4 import OutputTensor as OutputTensor04
-from bioimageio.spec.model.v0_5 import InputTensor as InputTensor05
-from bioimageio.spec.model.v0_5 import OutputTensor as OutputTensor05
+from bioimageio.spec._internal.io_utils import load_array
+from bioimageio.spec.model.v0_4 import InputTensorDescr as InputTensor04
+from bioimageio.spec.model.v0_4 import OutputTensorDescr as OutputTensor04
+from bioimageio.spec.model.v0_5 import InputTensorDescr as InputTensor05
+from bioimageio.spec.model.v0_5 import OutputTensorDescr as OutputTensor05
 
 InputTensor = Union[InputTensor04, InputTensor05]
 OutputTensor = Union[OutputTensor04, OutputTensor05]
@@ -103,7 +104,7 @@ def to_channel_last(image):
 def load_image(in_path, axes: Sequence[str]) -> DataArray:
     ext = os.path.splitext(in_path)[1]
     if ext == ".npy":
-        im = np.load(in_path)
+        im = load_array(in_path)
     else:
         is_volume = "z" in axes
         im = imageio.volread(in_path) if is_volume else imageio.imread(in_path)

bioimageio/core/resource_tests.py

@@ -9,7 +9,6 @@
 import numpy
 import numpy as np
 import xarray as xr
-from marshmallow import ValidationError
 
 from bioimageio.core import __version__ as bioimageio_core_version
 from bioimageio.core import load_raw_resource_description, load_resource_description
@@ -25,6 +24,7 @@
     ResourceDescription,
 )
 from bioimageio.spec import __version__ as bioimageio_spec_version
+from bioimageio.spec._internal.io_utils import load_array
 from bioimageio.spec.model.raw_nodes import WeightsFormat
 from bioimageio.spec.shared import resolve_source
 from bioimageio.spec.shared.common import ValidationWarning
@@ -161,8 +161,8 @@ def _test_model_inference(model: Model, weight_format: str, devices: Optional[Li
     tb: Optional = None
     with warnings.catch_warnings(record=True) as all_warnings:
         try:
-            inputs = [np.load(str(in_path)) for in_path in model.test_inputs]
-            expected = [np.load(str(out_path)) for out_path in model.test_outputs]
+            inputs = [load_array(str(in_path)) for in_path in model.test_inputs]
+            expected = [load_array(str(out_path)) for out_path in model.test_outputs]
 
             assert len(inputs) == len(model.inputs)  # should be checked by validation
             input_shapes = {}
@@ -362,7 +362,7 @@ def debug_model(
         bioimageio_model=model, devices=devices, weight_format=weight_format
     )
     inputs = [
-        xr.DataArray(np.load(str(in_path)), dims=input_spec.axes)
+        xr.DataArray(load_array(str(in_path)), dims=input_spec.axes)
         for in_path, input_spec in zip(model.test_inputs, model.inputs)
     ]
     input_dict = {input_spec.name: input for input_spec, input in zip(model.inputs, inputs)}
@@ -383,7 +383,7 @@ def debug_model(
         outputs = [outputs]
 
     expected = [
-        xr.DataArray(np.load(str(out_path)), dims=output_spec.axes)
+        xr.DataArray(load_array(str(out_path)), dims=output_spec.axes)
         for out_path, output_spec in zip(model.test_outputs, model.outputs)
     ]
     if len(outputs) != len(expected):

bioimageio/core/utils.py

@@ -7,7 +7,7 @@
 
 from bioimageio.spec.model import v0_4, v0_5
 from bioimageio.spec.model.v0_5 import TensorId
-from bioimageio.spec.utils import download
+from bioimageio.spec.utils import download, load_array
 
 # @singledispatch
 # def is_valid_tensor(description: object, tensor: Union[NDArray[Any], xr.DataArray]) -> bool:
@@ -24,7 +24,7 @@ def get_test_input_tensors(model: object) -> List[xr.DataArray]:
 
 @get_test_input_tensors.register
 def _(model: v0_4.Model):
-    data = [np.load(download(ipt).path) for ipt in model.test_inputs]
+    data = [load_array(download(ipt).path) for ipt in model.test_inputs]
     assert all(isinstance(d, np.ndarray) for d in data)
 
 

tests/prediction_pipeline/test_measures.py

@@ -6,16 +6,16 @@
 import pytest
 import xarray as xr
 
-from bioimageio.core import statistical_measures
+from bioimageio.core import stat_measures
 from bioimageio.core.prediction_pipeline._measure_groups import get_measure_groups
 from bioimageio.core.prediction_pipeline._utils import PER_DATASET, PER_SAMPLE
-from bioimageio.core.statistical_measures import Mean, Percentile, Std, Var
+from bioimageio.core.stat_measures import Mean, Percentile, Std, Var
 
 
 @pytest.mark.parametrize("name_axes", product(["mean", "var", "std"], [None, ("x", "y")]))
 def test_individual_normal_measure(name_axes):
     name, axes = name_axes
-    measure = getattr(statistical_measures, name.title())(axes=axes)
+    measure = getattr(stat_measures, name.title())(axes=axes)
     data = xr.DataArray(np.random.random((5, 6, 3)), dims=("x", "y", "c"))
 
     expected = getattr(data, name)(dim=axes)
@@ -26,7 +26,7 @@ def test_individual_normal_measure(name_axes):
 @pytest.mark.parametrize("axes_n", product([None, ("x", "y")], [0, 10, 50, 100]))
 def test_individual_percentile_measure(axes_n):
     axes, n = axes_n
-    measure = statistical_measures.Percentile(axes=axes, n=n)
+    measure = stat_measures.Percentile(axes=axes, n=n)
     data = xr.DataArray(np.random.random((5, 6, 3)), dims=("x", "y", "c"))
 
     expected = data.quantile(q=n / 100, dim=axes)