Comments (4)
bioimageio.spec defines the 'model RDF', where you find the inputs
field: https://github.com/bioimage-io/spec-bioimage-io/blob/gh-pages/model_spec_0_4.md#inputs
thus, for a given model resource you could use model = bioimageio.spec.load_raw_resource_description(model_rdf)
and then check model.inputs
.
To extend the inputs/outputs metadata we have this issue: bioimage-io/spec-bioimage-io#290
from core-bioimage-io-python.
So, in general, if inputs.shape.min
on the axis that corresponds to channel in inputs.axes
will always informal number of required channels?
(If explicit shape is provided then, it could be read from this)
from core-bioimage-io-python.
yes, you probably want to double check that inputs.shape.step
has a zero in the channel dim, otherwise the model would accept a range of input channels (which you probably don't want to support for now. I don't think any current model has this edge case).
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please reopen if there are more questions!
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Related Issues (20)
- validate (citation) dois
- VALUE is not a is not a valid RESUNIT HOT 12
- Better default io names in build_model() HOT 12
- Implement sha256 check for the model
- MONAI translation to BioImage format HOT 1
- Image normalization causing test_model test failure HOT 3
- Provide our CI testing environment as docker containers
- validate markdown documentation HOT 5
- Reproducibility test for model creation fails HOT 3
- Hackathon 2023/10 notes HOT 2
- programmatic access for datasets
- Add support for release candidates and automatic mail updates
- developer documentation
- Investigate integration of aicsimageio
- Add/improve weight converters
- Loading model resource gives assertion error HOT 2
- Link in example broken HOT 1
- Running `test_model` raises TypeError: list indices must be integers or slices, not str HOT 1
- Improve weights conversion to ONNX HOT 1
- bug when `add_deepimagej_config=True` in `build_model` HOT 5
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