Finished code review

.gitattributes

@@ -33,4 +33,3 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
-nnunet_results/Dataset903_Task903_DLMUSEV2/nnUNetTrainer__nnUNetPlans__3d_fullres/crossval_results_folds_0/summary.json filter=lfs diff=lfs merge=lfs -text

.github/workflows/python-publish.yml

@@ -0,0 +1,40 @@
+name: Upload Python Package
+
+on: workflow_dispatch
+
+permissions:
+  contents: read
+  id-token: write # Allow GitHub to mint tokens
+
+jobs:
+  pypi-publish:
+    name: Upload release to PyPI
+    runs-on: ubuntu-latest # Can use macos-latest if needed
+
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v2
+
+      - name: Set up Python
+        uses: actions/setup-python@v3
+        with:
+          python-version: "3.x"
+
+      - name: Install dependencies
+        run: |
+          pip install setuptools
+          pip install twine
+          pip install wheel
+          sudo apt-get install jq
+
+      - name: Clean previous builds
+        run: rm -rf dist
+
+      - name: Build package
+        run: python setup.py sdist bdist_wheel
+
+      - name: Publish package to PyPI
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+        run: twine upload --repository-url https://upload.pypi.org/legacy/ dist/*

README.md

@@ -20,40 +20,13 @@ cd DLMUSE
 pip install -e .
 ```
 
-### Using docker(OUTDATED)
-
-```bash
-docker pull aidinisg/dlmuse:0.0.1
-```
-
 ## Usage
 
-A pre-trained nnUNet model can be found in the [DLMUSEV2-1.0.0 release](https://github.com/CBICA/DLMUSE/releases/tag/v1.0.0). Feel free to use it under the package's [license](LICENSE).
+A pre-trained nnUNet model can be found at our [hugging face account](https://huggingface.co/nichart/DLMUSE/tree/main) or at the [DLMUSEV2-1.0.0 release](https://github.com/CBICA/DLMUSE/releases/tag/v1.0.0). Feel free to use it under the package's [license](LICENSE).
 
 ### From command line
 ```bash
-DLMUSE -i "image_folder" -o "path to output folder" -m "path to model weights" -f 0 -tr nnUNetTrainer -c 3d_fullres -p nnUNetPlans -d "id" -device cuda/cpu/mps
-```
-
-### Using the docker container(OUTDATED)
-
-In the [docker container](https://hub.docker.com/repository/docker/aidinisg/dlmuse/general), the default model is included, but you can also provide your own.
-
-Without providing a model:
-
-```bash
-docker run --gpus all -it --rm -v /path/to/local/input:/workspace/input \
-                               -v /path/to/local/output:/workspace/output \
-                               aidinisg/dlmuse:0.0.1  -i input/ -o output/
-```
-
-Providing a model:
-
-```bash
-docker run --gpus all -it --rm -v /path/to/local/model:/workspace/model \
-                               -v /path/to/local/input:/workspace/input \
-                               -v /path/to/local/output:/workspace/output \
-                               aidinisg/dlmuse:0.0.1  -i input/ -o output/  --model model/
+DLMUSE -i "image_folder" -o "path to output folder" -device cuda/mps/cpu
 ```
 
 ## Contact

nnunet_output/dataset.json

@@ -0,0 +1,11 @@
+{
+    "channel_names": {
+        "0": "MRI"
+    },
+    "file_ending": ".nii.gz",
+    "labels": {
+        "background": 0,
+        "class1": 1
+    },
+    "numTraining": 1806
+}