A trained Xception net on Tensorflow/Keras to classify conus marine snails.
Know more »»Welcome to the DEEP Open Catalog!
DEEP-Hybrid-DataCloud is a project that aims to deliver a framework to easily develop Machine Learning and Deep Learning modules on top of e-Infrastructures. In the DEEP Open Catalog you can find ready to use modules in a variety of domains. These modules can be executed on your local laptop, on a production server or on top of e-Infrastrucutres supporting the DEEP-Hybrid-DataCloud stack.
Browse the list of available modules and pick the one of your choice.
The DEEP Generic Container is a good starting point to see how the API looks like (but it does not provide any functionality at all).
$ docker search deephdc
$ docker run -ti -p 5000:5000 deephdc/deep-oc-generic-container$ udocker search deephdc
$ udocker run -p 5000:5000 deephdc/deep-oc-generic-containerNeed GPU access?
Use nvidia-docker together with Docker:$ nvidia-docker run -ti -p 5000:5000 deephdc/deep-oc-generic-container$ udocker pull deephdc/deep-oc-generic-container
$ udocker create --name=deep-oc-generic-container deephdc/deep-oc-generic-container
$ udocker setup --nvidia deep-oc-generic-container
$ udocker run -p 5000:5000 deep-oc-generic-containerhttp://127.0.0.1:5000/.
A trained Xception net on Tensorflow/Keras to classify conus marine snails.
Know more »»Massive Online Data Streams analysis.
Know more »»A trained Xception net on Tensorflow/Keras to classify phytoplankton.
Know more »»A trained Xception net on Tensorflow/Keras to classify plants.
Know more »»A trained Xception net on Tensorflow/Keras to classify seeds.
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