updated Dockerfile and dependencies

.github/workflows/docker-image.yml

@@ -1,15 +1,15 @@
 name: Docker Image CI
 
-on:
-  push:
-    branches: 
-        - "master"
-        - "remove_old_models"
-  pull_request:
-    branches: [ "master" ]
-  workflow_dispatch:
+#on:
+#  push:
+#    branches: 
+#        - "master"
+#        - "remove_old_models"
+#  pull_request:
+#    branches: [ "master" ]
+#  workflow_dispatch:
 
-# on: null # Disables all triggers for this workflow
+on: null # Disables all triggers for this workflow
 
 jobs:
   push_to_registry:

Dockerfile

@@ -5,23 +5,62 @@ ENV DEBIAN_FRONTEND=noninteractive
 ARG USER_ID
 ARG GROUP_ID
 ARG UNAME
-RUN groupadd -g $GROUP_ID -o $UNAME
+RUN groupadd -g $GROUP_ID -o user
 RUN useradd -m -u $USER_ID -g $GROUP_ID -o -s /bin/bash $UNAME
-RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
+USER root
+RUN set -ex; \
+    for i in $(seq 1 10); do \
+        apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys A4B469963BF863CC && break || sleep 15; \
+    done
 RUN apt-get update --allow-unauthenticated
 RUN apt-get install -y git
 WORKDIR /opt
-RUN mkdir /opt/virtualenv
-RUN python3 -m venv /opt/virtualenv
-COPY requirements.txt /opt/virtualenv
-RUN /opt/virtualenv/bin/pip install --upgrade pip
-RUN /opt/virtualenv/bin/pip install -r /opt/virtualenv/requirements.txt
+#ENV PATH="/opt/miniconda3/bin:${PATH}"
+#ARG PATH="/opt/miniconda3/bin:${PATH}"
+#RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.11.0-Linux-x86_64.sh \ 
+#    &&  bash  Miniconda3-py39_4.11.0-Linux-x86_64.sh -p /opt/miniconda3 -b  \
+#    &&  rm -vf Miniconda3-py39_4.11.0-Linux-x86_64.sh
+#RUN conda install -y pytorch torchvision -c pytorch 
+#RUN python -c 'import torch;print(torch.backends.cudnn.version())'
+#RUN apt-get install git
+RUN git clone https://github.com/Project-MONAI/MONAI.git  /opt/monai
+WORKDIR /opt/monai
+RUN git checkout b7403ee5a91caef158181a9dcc2b9b1453f9dbdd
+RUN python setup.py install
+#RUN conda install -y jupyter matplotlib 
+#RUN conda install -y -c conda-forge nibabel 
+#RUN conda install -y ignite -c pytorch 
+#RUN conda install -y scikit-image
+#RUN conda install -y -c conda-forge tensorboard gdown python-lmdb 
+RUN echo "export PATH=/opt/miniconda3/bin:${PATH}" >> /etc/profile
+USER $UNAME
+RUN pip install --upgrade pip
+RUN pip install -q "monai-weekly[nibabel, tqdm]==1.4.dev2347"
+RUN pip install -q nilearn==0.10.2 
+RUN pip install notebook==7.0.6 jupyterlab==4.0.9 matplotlib==3.7.4
+WORKDIR /mnt
+#mongo
+USER root
+#RUN conda install -c anaconda pymongo qgrid dnspython
+RUN pip install pymongo==4.6.0  dnspython==2.4.2 qgrid==1.3.1 scikit-image==0.21.0
+RUN pip install pytorch-ignite==0.4.13
+##RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
+##RUN mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
+##RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
+##RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"
+##RUN apt-get update
+##
+##RUN apt-get install libnccl2 libnccl-dev
+RUN pip install ipdb==0.13.13
+RUN pip install scipy==1.10.1
 RUN git clone https://github.com/Project-MONAI/tutorials.git /opt/monai-tutorials
 WORKDIR /opt/monai-tutorials 
+RUN ls
 RUN git checkout c501cbef2c291b4920b9a8ad3e4a67f334f79f30
-COPY mindGlide/config/task_params.py /opt/monai-tutorials/modules/dynunet_pipeline/
+COPY  mindGlide/config/task_params.py /opt/monai-tutorials/modules/dynunet_pipeline/
 WORKDIR /mnt
+RUN pip install nibabel==5.1.0
 USER $UNAME
 COPY scripts/entrypoint.sh /entrypoint.sh 
 COPY ./ /opt/mindGlide
-ENTRYPOINT [ "/entrypoint.sh" ]
+ENTRYPOINT [ "/entrypoint.sh" ]

README.md

@@ -117,17 +117,24 @@ more information about the models:
 
 | Model name and path in the models directory | Description | Dataset |
 |-|-|-|
-| /opt/mindGlide/models/model_0_net_key_metric=0.7627.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_2_net_key_metric=0.7541.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_2_net_key_metric=0.7579.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_3_net_key_metric=0.7713.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_3_net_key_metric=0.7717.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_4_net_key_metric=0.7645.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_5_net_key_metric=0.7866.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_6_net_key_metric=0.7723.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_7_net_key_metric=0.7634.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_8_net_key_metric=0.7489.pt | trained on dataset 1 | IPMSA |
-| /opt/mindGlide/models/model_9_net_key_metric=0.7738.pt | trained on dataset 1 | IPMSA |
+| /opt/mindGlide/models/_20240404_conjurer_trained_dice_7733.pt | trained on dataset 1 (This model is 10 times larger than the previous models) | IPMSA |
+
+### 📬 Citation
+
+If you use MindGlide please cite this paper:
+
+```bibtex
+@article {Goebl2024.03.29.24305083,
+	author = {Philipp Goebl and Jed Wingrove and Omar Abdelmannan and Barbara Brito Vega and Jonathan Stutters and Silvia Da Graca Ramos and Owain Kenway and Thomas Rosoor and Evangeline Wassmer and Jeremy Chataway and Douglas Arnold and Louis Collins and Cheryl Hemmingway and Sridar Narayanan and Declan Chard and Juan Eugenio Iglesias and Frederik Barkhof and Yael Hacohen and Alan Thompson and Daniel Alexander and Olga Ciccarelli and Arman Eshaghi},
+	title = {Repurposing Clinical MRI Archives for Multiple Sclerosis Research with a Flexible, Single-Modality Approach: New Insights from Old Scans},
+	elocation-id = {2024.03.29.24305083},
+	year = {2024},
+	doi = {10.1101/2024.03.29.24305083},
+	URL = {https://www.medrxiv.org/content/early/2024/03/30/2024.03.29.24305083},
+	eprint = {https://www.medrxiv.org/content/early/2024/03/30/2024.03.29.24305083.full.pdf},
+	journal = {medRxiv}
+} 
+```
 
 ### Acknowledgements
 

build_docker_script.sh

@@ -1 +1 @@
-docker build  --build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) --build-arg UNAME="arman" -t armaneshaghi/mind-glide:sep2023 .
+docker build  --build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) --build-arg UNAME="user" -t mspinpoint/mindglide:june2024 .