PicStork Super 30 Challenge

Urban Planning → MultiClass Detection

Title: The Art of Multiclass Detection using PicStork

Multiclass Detection is akin to an arrangement when it comes to how the world appears to us. It’s an integrated work that involves more than just detecting one thing. The key is to understand the diversity of the eleven distinct classes that exist in GeoTiff. Now, let’s explore the significance of Multiclass Detection, where each identified class contributes uniquely to a visual work of art.

Number of annotations per instances:

  • Cars: 70
  • Spaces: 68
  • Bushes: 25
  • Trees: 23
  • Rooftops: 11
  • Lane Markings: 6
  • Dust Bins: 4
  • Zebra Crossings: 3
  • Bikes: 3
  • Buses: 1
  • Shades: 1