Python package for data.world

Reference implementation of the APIs defined in ga4gh-schemas. RETIRED 2018-01-24

Use computer vision inference in the Intel® Distribution of OpenVINO™ toolkit to provide analytics on customer engagement, store traffic, and shelf inventory.

Our production-ready reference implementation for Django Projects

Observe workers as they pass in front of a camera to determine if they have adequate safety protection.

Build a solution to analyze customer expressions and reactions to product advertising collateral that is positioned on retail shelves.

Authorization Server Implementation in Python supporting OAuth 2.0 & OpenID Connect

Predict performance issues with manufacturing equipment motors. Perform local or cloud analytics of the issues found, and then display the data on a user interface to determine when failures might arise.

Monitor mechanical bolts as they move down a conveyor belt. When a bolt of an irregular size is detected, this solution emits an alert.

Development of the Gellish Communicator reference application and tools for universal data exchange and data integration supporting Formal English and other Gellish formalized natural languages.

Monitor three different streams of video that count people inside and outside of a facility. This application also counts product inventory.

Secure work areas and send alerts if someone enters the restricted space.

Use a visual heat or motion map to count the number of people that enter and exit a store, factory, or warehouse aisle.

Detect various irregularities of a product as it moves along a conveyor belt.

CKAN extension for data.world

Build a solution that recognizes people within a specific area and measures the distance between them. Get an alert if the distance is less than a specified amount.

Implement and use Intel® hardware platforms for video decoding, encoding, and optimization using various media stacks.

Segment brain tumors in raw MRI images by applying the U-Net architecture.

Predict performance issues with manufacturing equipment motors. Perform local or cloud analytics of the issues found, and then display the data on a user interface to determine when failures might arise.

Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.