Release v0.4.0

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.0
+current_version = 0.4.0
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)((?P<release>a|b|rc)(?P<build>\d+))?
 serialize = 
 	{major}.{minor}.{patch}{release}{build}

docs/source/getting_started/tutorials/06_monai_bundle_app.md

@@ -0,0 +1,69 @@
+# 6) Creating a Segmentation app consuming a MONAI Bundle
+
+## Setup
+
+```bash
+# Create a virtual environment with Python 3.7.
+# Skip if you are already in a virtual environment.
+# (JupyterLab dropped its support for Python 3.6 since 2021-12-23.
+#  See https://github.com/jupyterlab/jupyterlab/pull/11740)
+conda create -n monai python=3.7 pytorch torchvision jupyterlab cudatoolkit=11.1 -c pytorch -c conda-forge
+conda activate monai
+
+# Launch JupyterLab if you want to work on Jupyter Notebook
+jupyter-lab
+```
+
+## Executing from Jupyter Notebook
+
+```{toctree}
+:maxdepth: 4
+
+../../notebooks/tutorials/06_monai_bundle_app.ipynb
+```
+
+```{raw} html
+<p style="text-align: center;">
+    <a class="sphinx-bs btn text-wrap btn-outline-primary col-md-6 reference external" href="../../_static/notebooks/tutorials/06_monai_bundle_app.ipynb">
+        <span>Download 06_monai_bundle_app.ipynb</span>
+    </a>
+</p>
+```
+
+## Executing from Shell
+
+```bash
+# Clone the github project (the latest version of main branch only)
+git clone --branch main --depth 1 https://github.com/Project-MONAI/monai-deploy-app-sdk.git
+
+cd monai-deploy-app-sdk
+
+# Install monai-deploy-app-sdk package
+pip install monai-deploy-app-sdk
+
+# Download/Extract ai_spleen_bundle_data zip file from https://drive.google.com/file/d/1cJq0iQh_yzYIxVElSlVa141aEmHZADJh/view?usp=sharing
+
+# Download ai_spleen_bundle_data.zip
+pip install gdown
+gdown https://drive.google.com/uc?id=1cJq0iQh_yzYIxVElSlVa141aEmHZADJh
+
+# After downloading ai_spleen_bundle_data.zip from the web browser or using gdown,
+unzip -o ai_spleen_bundle_data.zip
+
+# Install necessary packages from the app; note that numpy-stl and trimesh are only
+# needed if the application uses the STL Conversion Operator
+pip install monai pydicom SimpleITK Pillow nibabel scikit-image numpy-stl trimesh
+
+# Local execution of the app directly or using MONAI Deploy CLI
+python examples/apps/ai_spleen_seg_app/app.py -i dcm/ -o output -m model.ts
+# or alternatively,
+monai-deploy exec ../examples/apps/ai_spleen_seg_app/app.py -i dcm/ -o output -m model.ts
+
+# Package app (creating MAP docker image) using `-l DEBUG` option to see progress.
+# This assumes that nvidia docker is installed in the local machine.
+# Please see https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker to install nvidia-docker2.
+monai-deploy package examples/apps/ai_spleen_seg_app --tag seg_app:latest --model model.ts -l DEBUG
+
+# Run the app with docker image and input file locally
+monai-deploy run seg_app:latest dcm/ output
+```

docs/source/release_notes/index.md

@@ -4,6 +4,13 @@
 :hidden:
 :maxdepth: 2
 
+```
+## Version 0.4
+
+```{toctree}
+:maxdepth: 1
+
+v0.4.0
 ```
 ## Version 0.3
 

docs/source/release_notes/v0.4.0.md

@@ -0,0 +1,34 @@
+# Version 0.4.0
+
+
+
+## What's new in 0.4.0
+- New operator to automate inference with the newly introduced [MONAI Bundle](https://docs.monai.io/en/stable/whatsnew_0_9.html)
+
+### MONAI Bundle Inference Operator
+
+The new operator, `MONAI Bundle Inference Operator`, is intended to automate the inference with a MONAI Bundle in TorchScript with the following functionalities:
+- Parse the model metadata and extra configuration data in the TorchScript file
+- Instanciate MONAI transforms and inferer objects per bundle configuration data
+- Convert input/output of the operator to and from model network input
+- Support named model and can be used in a multi-model application
+
+The example [spleen segmentation application](https://github.com/Project-MONAI/monai-deploy-app-sdk/tree/main/examples/apps/ai_spleen_seg_app) was accordingly updated to demonstrate the use of this new operator with the newly published [Spleen CT Segmentation Bundle](https://github.com/Project-MONAI/model-zoo/tree/dev/models/spleen_ct_segmentation).
+
+More details are in the [tutorial](https://github.com/Project-MONAI/monai-deploy-app-sdk/blob/main/notebooks/tutorials/06_monai_bundle_app.ipynb).
+
+## What's fixed/updated
+
+- [[FEA] A generic operator to automate inference execution with a MONAI Bundle](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/286)
+- [[FEA] Integrating Model Zoo and MMAR](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/213)
+- [[FEA] Multi-model support in an application built with MONAI Deploy App SDK](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/244)
+- [[DOC] Missing python dependencies for the segmentation app](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/299) and the [duplicate](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/305)
+- [mednist_app:latest -- No module named 'nibabel'](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/302)
+- [[DOC] Series Selector dictionary](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/300)
+
+## Additional information
+Please visit [GETTING STARTED](/getting_started/index) guide and follow the tutorials.
+
+You can learn more about SDK usage through [DEVELOPING WITH SDK](/developing_with_sdk/index).
+
+Please let us know how you like it and what could be improved by [submitting an issue](https://github.com/Project-MONAI/monai-deploy-app-sdk/issues/new/choose) or [asking questions](https://github.com/Project-MONAI/monai-deploy-app-sdk/discussions)