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A reference implementation of an AI lab.

Project description

TensorSpace is a reference implementation of an artificial intelligence lab.

Why?

I was tired of setting up ad hoc environments for various research experiments. I wanted a solution that can turn any “computer” into a research environment that I can use right away.

Features

  • Downloads and normalizes datasets. Currently only COCO, but more coming. Saves everything into a nice organized directory structure.
  • Single annotation schema for all datasets. You don’t need to research with just one dataset at a time anymore. You do queries like “give me all images with bounding boxes from all datasets”.
  • Automatically preprocess vectors or other intermidate datasets.
  • Coming soon: Demos and models that use the data.
  • Coming soon: GraphQL API for running models
  • Coming soon: Multiple deployment targets. This will include Kubernetes.

Installation

pip install tensorspace

Usage

tensorspace up

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
tensorspace-0.0.3.tar.gz (2.2 kB) Copy SHA256 hash SHA256 Source None Jun 14, 2018

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