Merge pull request #360 from bioimage-io/bump_post

Release 0.5.10

Author: FynnBe

README.md

@@ -7,45 +7,52 @@ Python specific core utilities for running models in the [BioImage Model Zoo](ht
 ### Via Conda
 
 The `bioimageio.core` package can be installed from conda-forge via
+
 ```
 conda install -c conda-forge bioimageio.core
 ```
+
 if you don't install any additional deep learning libraries, you will only be able to use general convenience functionality, but not any functionality for model prediction.
 To install additional deep learning libraries use:
 
 * Pytorch/Torchscript:
+
   ```bash
   # cpu installation (if you don't have an nvidia graphics card)
   conda install -c pytorch -c conda-forge bioimageio.core pytorch torchvision cpuonly
 
   # gpu installation (for cuda 11.6, please choose the appropriate cuda version for your system)
-  conda install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.6 
+  conda install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.6
   ```
-  Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to [pytorch.org](https://pytorch.org/).
 
+  Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to [pytorch.org](https://pytorch.org/).
 
 * Tensorflow
+
   ```bash
   # currently only cpu version supported
   conda install -c conda-forge bioimageio.core tensorflow
   ```
 
 * ONNXRuntime
+
   ```bash
   # currently only cpu version supported
   conda install -c conda-forge bioimageio.core onnxruntime
   ```
-  
+
 ### Via pip
 
 The package is also available via pip:
+
 ```
 pip install bioimageio.core
 ```
 
 ### Set up Development Environment
 
 To set up a development conda environment run the following commands:
+
 ```
 conda env create -f dev/environment-base.yaml
 conda activate bio-core-dev
@@ -57,40 +64,52 @@ There are different environment files that only install tensorflow or pytorch as
 ## Command Line
 
 `bioimageio.core` installs a command line interface for testing models and other functionality. You can list all the available commands via:
+
 ```
 bioimageio
 ```
 
 Check that a model adheres to the model spec:
+
 ```
 bioimageio validate <MODEL>
 ```
 
 Test a model (including prediction for the test input):
+
 ```
 bioimageio test-model <MODEL>
 ```
 
 Run prediction for an image stored on disc:
+
 ```
 bioimageio predict-image <MODEL> --inputs <INPUT> --outputs <OUTPUT>
 ```
 
 Run prediction for multiple images stored on disc:
+
 ```
 bioimagei predict-images -m <MODEL> -i <INPUT_PATTERN> - o <OUTPUT_FOLDER>
 ```
-`<INPUT_PATTERN>` is a `glob` pattern to select the desired images, e.g. `/path/to/my/images/*.tif`.
 
+`<INPUT_PATTERN>` is a `glob` pattern to select the desired images, e.g. `/path/to/my/images/*.tif`.
 
 ## From python
 
 `bioimageio.core` is a python library that implements loading models, running prediction with them and more.
 To get an overview of this functionality, check out the example notebooks:
-- [example/model_usage](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/model_usage.ipynb) for how to load models and run prediction with them
-- [example/model_creation](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/model_creation.ipynb) for how to create bioimage.io compatible model packages
-- [example/dataset_statistics_demo](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/dataset_statistics_demo.ipynb) for how to use the dataset statistics for advanced pre-and-postprocessing
+
+* [example/model_usage](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/model_usage.ipynb) for how to load models and run prediction with them
+* [example/model_creation](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/model_creation.ipynb) for how to create bioimage.io compatible model packages
+* [example/dataset_statistics_demo](https://github.com/bioimage-io/core-bioimage-io-python/blob/main/example/dataset_statistics_demo.ipynb) for how to use the dataset statistics for advanced pre-and-postprocessing
 
 ## Model Specification
 
-The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.
+The model specification and its validation tools can be found at <https://github.com/bioimage-io/spec-bioimage-io>.
+
+## Changelog
+
+### 0.5.10
+
+* [Fix critical bug in predict with tiling](https://github.com/bioimage-io/core-bioimage-io-python/pull/359)

bioimageio/core/VERSION

@@ -1,3 +1,3 @@
 {
-    "version": "0.5.9"
+    "version": "0.5.10"
 }