Docker container with a bootstrapped installation of Anaconda (based on Python 3.5) that is ready to use. The Anaconda distribution is installed into the /opt/conda folder and ensures that the default user has the conda command in their path. Anaconda is the leading open data science platform powered by Python. The open source version of Anaconda is a high performance distribution and includes over 100 of the most popular Python packages for data science. Additionally, it provides access to over 720 Python and...

Pull command: docker pull continuumio/anaconda3

License : GNU AGPLv3

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors. Check out the project site for all the details like DIY Deep Learning for Vision with Caffe Tutorial Documentation BVLC reference models and the community model zoo Installation instructions and step-by-step examples.   License and Citation Caffe is released under the BSD 2-Clause license. The BVLC reference models are...

Pull command: docker pull bvlc/caffe

License : GNU AGPLv3

DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments DeepDIVA is an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a researcher can either reproduce a given experiment with a very limited amount of information or share their own experiments with...

License : GNU AGPLv3

This tool takes a color input image (preferrably from a document) and turns it into a binarized version. A container can be executed the following way: docker run -it --rm -v /home/user/Documents/image.jpg:/input/input.jpg -v /home/user/Documents/:/output/ sh /input/ /input/input.jpg /output/ The file located at /home/user/Documents/image.jpeg will be used as input and the resulting binarized image will be located at /home/user/Documents/otsuBinaryImage.jpeg So...

Pull command: docker pull

License : GNU LGPLv3

Jupyter Notebook Scientific Python Stack + Tensorflow + Tensorboard This docker image is based on Tensorflow Notebook, and gives the ability ofStarting tensorboard in Jupyter notebook. jupyter-tensorboard extension github: Usage Pull tensorboard-notebook docker image and start a container: docker pull lspvic/tensorboard-notebook docker run -it --rm -p 8888:8888 lspvic/tensorboard-notebook Once tensorboard-notebook is started , you should be able to find the...

Pull command: docker pull lspvic/tensorboard-notebook

License : Apache License 2.0


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