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@@ -288,17 +288,33 @@ The package is also available via pip
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pip install "bioimageio.core[onnx,pytorch]"
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```
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### Set up Development Environment
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##🐍 Use in Python
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To set up a development conda environment run the following commands:
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`bioimageio.core` is a python package that implements prediction with bioimageio models
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including standardized pre- and postprocessing operations.
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These models are described by---and can be loaded with---the bioimageio.spec package.
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```console
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conda env create -f dev/env.yaml
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conda activate core
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pip install -e . --no-deps
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```
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In addition bioimageio.core provides functionality to convert model weight formats.
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There are different environment files available that only install tensorflow or pytorch as dependencies, see [dev folder](https://github.com/bioimage-io/core-bioimage-io-python/tree/main/dev).
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### Documentation
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[Here you find the bioimageio.core documentation.](https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/core.html)
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#### Presentations
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-[Create a model from scratch](https://bioimage-io.github.io/core-bioimage-io-python/presentations/create_ambitious_sloth.slides.html) ([source](https://github.com/bioimage-io/core-bioimage-io-python/tree/main/presentations))
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#### Examples
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<dl>
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<dt>Notebooks that save and load resource descriptions and validate their format (using <ahref="https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/spec.html">bioimageio.spec</a>, a dependency of bioimageio.core)</dt>
<imgsrc="https://colab.research.google.com/assets/colab-badge.svg"alt="Open In Colab"/>
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</a></dd>
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<dt>Use the described resources in Python with <ahref="https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/core.html">bioimageio.core</a></dt>
<imgsrc="https://colab.research.google.com/assets/colab-badge.svg"alt="Open In Colab"/>
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</dl>
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## 💻 Use the Command Line Interface
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bioimageio
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```
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For examples see [Getting started](#get-started).
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### CLI inputs from file
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For convenience the command line options (not arguments) may be given in a `bioimageio-cli.json`
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stats: inputs/dataset_statistics.json
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```
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## 🐍 Use in Python
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`bioimageio.core` is a python package that implements prediction with bioimageio models
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including standardized pre- and postprocessing operations.
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These models are described by---and can be loaded with---the bioimageio.spec package.
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In addition bioimageio.core provides functionality to convert model weight formats.
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## Set up Development Environment
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### Documentation
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[Here you find the bioimageio.core documentation.](https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/core.html)
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To set up a development conda environment run the following commands:
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#### Presentations
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- [Create a model from scratch](https://bioimage-io.github.io/core-bioimage-io-python/presentations/create_ambitious_sloth.slides.html) ([source](https://github.com/bioimage-io/core-bioimage-io-python/tree/main/presentations))
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```console
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conda env create -f dev/env.yaml
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conda activate core
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pip install -e . --no-deps
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```
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#### Examples
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<dl>
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<dt>Notebooks that save and load resource descriptions and validate their format (using <a href="https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/spec.html">bioimageio.spec</a>, a dependency of bioimageio.core)</dt>
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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</a></dd>
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<dt>Use the described resources in Python with <a href="https://bioimage-io.github.io/core-bioimage-io-python/bioimageio/core.html">bioimageio.core</a></dt>
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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</dl>
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There are different environment files available that only install tensorflow or pytorch as dependencies, see [dev folder](https://github.com/bioimage-io/core-bioimage-io-python/tree/main/dev).
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