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DeepRegNet / DeepReg

Medical image registration using deep learning
Apache License 2.0
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Making docker image of deepreg #777

Closed mianasbat closed 2 years ago

mianasbat commented 3 years ago

Hi, I noted that you provide the user with Dockerfile to build the image and then use it using docker. It would be nice if you make a docker image and keep it on dockerhub for each release of deepreg. This will be useful in at least two ways.

First is users do not have to build it on their machine and saving them one step. Second and more important is that maintaining the image. E.g. if a person is building the docker image of deepreg and at that time a specific package is not available on conda then it cant be build. Similarly if a package support is finished and its no more maintained then dockerfile will be outdated. However keeping an image on dockerhub will have a snapshot of working deepreg and all users will have to do is docker run deepreg:version_no.

mathpluscode commented 3 years ago

Hi @mianasbat thx for the advice, yes, we've been considering this, https://github.com/DeepRegNet/DeepReg/issues/608. Just recently I got occupied by other things.

Zhiyuan-w commented 3 years ago

=> [internal] load metadata for docker.io/tensorflow/tensorflow:2.3.1-gpu 12.4s => [auth] tensorflow/tensorflow:pull token for registry-1.docker.io 0.0s => [ 1/10] FROM docker.io/tensorflow/tensorflow:2.3.1-gpu@sha256:1d0736e46ae9a961c2111394a43e0bfd266e6151a90d613b6f86229cf01e40e5 0.0s => CACHED [ 2/10] RUN apt-get update 0.0s => CACHED [ 3/10] RUN apt-get install -y wget git && rm -rf /var/lib/apt/lists/* 0.0s => CACHED [ 4/10] RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && mkdir /root/.conda && bash Miniconda3-latest-Linux-x86_64.sh -b && rm -f Miniconda3-latest-Linux- 0.0s => CACHED [ 5/10] WORKDIR /app 0.0s => CACHED [ 6/10] RUN git clone https://github.com/DeepRegNet/DeepReg.git 0.0s => CACHED [ 7/10] WORKDIR DeepReg 0.0s => CACHED [ 8/10] RUN git pull 0.0s => CACHED [ 9/10] RUN conda env create -f environment.yml && conda init bash && echo "conda activate deepreg" >> /root/.bashrc 0.0s => CACHED [10/10] RUN /root/miniconda3/envs/deepreg/bin/pip install -e . 0.0s => exporting to image 0.1s => => exporting layers

It works today... I changed nothing. I met the issue, as loading metadata for docker.io/tensorflow/tensorflow:2.3.1-gpu. It gives the error that TensorFlow is not able to be loaded.

stale[bot] commented 3 years ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.