for deploy

.github/workflows/pypi_publish.yml

@@ -0,0 +1,31 @@
+# This workflow will upload a Python Package using Twine when a release is created
+# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
+
+name: Upload Python Package
+
+on:
+  release:
+    types: [created]
+
+jobs:
+  deploy:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.x'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+    - name: Build and publish
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

README.md

@@ -51,12 +51,22 @@ Key points about U-FISH:
 - [ ] Benchmarks
 - [ ] Documentation
 
-## Usage
+## Installation
 
 ```bash
 pip install ufish
 ```
 
+For inference using GPU:
+
+```bash
+pip install ufish[onnxruntime-gpu]
+```
+
+For training using GPU, you need to install PyTorch with CUDA support, see [PyTorch official website](https://pytorch.org/) for details.
+
+## Usage
+
 CLI usage:
 
 ```bash

requirements.txt

@@ -12,6 +12,5 @@ tensorboard
 imagecodecs
 onnx
 onnxruntime
-onnxruntime-gpu
 zarr
 ome-zarr

setup.py

@@ -80,6 +80,7 @@ def get_doc_requires():
     install_requires=get_install_requires(),
     extras_require={
         'dev': requires_dev,
+        'onnxruntime-gpu': ['onnxruntime-gpu'],
     },
     python_requires='>=3.9, <4',
     entry_points={