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groundwork-detection

ARGO internship project to use http://customvision.ai to detect features from Urban street imagery.

Why

According to a recent Economist op-ed, small improvements in "Maintenance, management of state assets and public-sector accounting", could lead to large economic gains for cities, states, and entire nations.

We believe that local and state governments should be capable of auditing the urban environment using common-sense digital tools and leveraging advances in machine learning, responsibly towards the next-generation of Maintenance, management of state assets and public-sector accounting.

What

Using street view imagery, develop a computer vision model that is trained on three specific elements of urban infrastructure, namely:

  1. Detection of US street signage.
  2. Road width estimates.
  3. Detection and counting of Yellow Taxis on NYC streets.

How

Use http://customvision.ai - an easy-to-use computer vision toolkit developed by Microsoft.

When

Week 1 - Orientation

Week 2 - Train & Test

  • Upload training imagery to customvision interface.
  • Label what you intend to detections from the uploaded imagery.
  • Test the accuracy of your trained model.
  • Iterate towards better precision and recall.

Week 3 and beyond - Results

  • Parse results from customvision output into a more readable format.
  • Deploy your trained model to "audit" a specific geography. (For consistency, we will choose this area for you).
  • Prepare blog to document your journey. What worked, What did not. Ideas for future improvement / applications etc.

Who

ARGO project supervisor: Varun Adibhatla

CUSP Students

Team 1 - Detection of US street signage:

  • Yushi Chen, Karan Saini, Sung Hoon Yang

Team 2- Detection and counting of Yellow Taxis on NYC streets:

  • Junjie Cai, Urwa Muaz, Manrique Vargas

Operational Roles

  • Project scribe: CUSP student who will take notes during check-in and manage the github repo (code,readme, issues)
  • Project logistics: CUSP student who ensures meetings are scheduled and handles conference/video calls.

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Use customvision.ai to detect specific elements of urban infrastructure.

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