DeepCell: Deep learning for image segmentation in live cell imaging experiments
1.9K
https://github.com/CovertLab/DeepCell https://simtk.org/projects/deepcell
To run the Jupyter Notebooks, execute the command: "sudo nvidia-docker run -it -p 9999:9999 deepcell" and open a web browser to localhost:9999
Dockerfile: FROM nvidia/cuda:8.0-cudnn5-devel
MAINTAINER David Van Valen
ENV HOME /root ENV PYENV_ROOT /root/.pyenv ENV PATH /root/.pyenv/shims:/root/.pyenv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin
WORKDIR $HOME
RUN apt-get -y update && apt-get install -y git curl g++ make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev
RUN curl -L https://raw.githubusercontent.com/yyuu/pyenv-installer/master/bin/pyenv-installer | bash
RUN CONFIGURE_OPTS=--enable-shared pyenv install 2.7.4
RUN git clone https://github.com/CovertLab/DeepCell.git
WORKDIR $HOME/DeepCell
RUN pyenv local 2.7.4
RUN pyenv virtualenv DeepCell
RUN pyenv local DeepCell
RUN pip install numpy
RUN pip install scipy
RUN pip install scikit-learn scikit-image matplotlib palettable libtiff tifffile h5py ipython[all]
RUN pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git
RUN pip install keras pywavelets mahotas
RUN mkdir $HOME/.keras && echo '{"image_dim_ordering": "th", "epsilon": 1e-07, "floatx": "float32", "backend": "theano"}' >> $HOME/.keras/keras.json
RUN echo '[global]\ndevice = gpu\nfloatX = float32' > $HOME/.theanorc
WORKDIR $HOME/DeepCell/keras_version
CMD jupyter notebook --port 9999 --no-browser --ip=*
Content type
Image
Digest
Size
3.4 GB
Last updated
about 10 years ago
docker pull vanvalen/deepcell