Imagerie
A TensorFlow training interface

Automate quality assurance with image detection

  • Built interface and middleware components to robust automated image training program
  • Express Server as proxy service to upload / download photos from Minio / AWS S3 and other storage services
  • Drop and Drop photo library manager for building trainings from remote and local photos
  • Customized Tree component for infinite nesting of tags under photos, and easier review of tag and photo collections with counts and average region sizes
  • Customized drawing component for creating, dragging, and resizing tags with 0 - 400% magnified zoom window
  • User defined categories, tag names, and tool sets
  • Automated demo builder with customizing parameters
  • Webpack 4 hotloading development environment with testing, production and development build scripts for packing and deployment

Started: 2018-05-01

Launched/Lasted:: 2018-12-31

Dev: http://imagerie.taylormadetraffic.com/training/demo

Tools: Node.js, Express.js, React.js, Bootstrap, AWS S3, Docker, Webpack 4, TensorFlow, Kubernetes, Google Cloud Platform

Team: E.A.Taylor: Front-End. Sam Silverberg: TensorFlow. Aaron Silverberg: Product Development.

Client: Refined Motion

Copyright: Refined Motion

Industries: technology, analytics, robotics, manufacturing