US 12,223,574 B2
Automatic area detection
Mohammad Soltani, Ontario (CA); Farid Mirahadi, North York (CA); Azadeh Yazdan Panah Gohar Rizi, Richmond Hill (CA); and Fiona Liu, North York (CA)
Assigned to Procore Technologies, Inc., Carpinteria, CA (US)
Filed by Procore Technologies, Inc., Carpinteria, CA (US)
Filed on Dec. 28, 2023, as Appl. No. 18/399,334.
Application 18/399,334 is a continuation of application No. 17/883,555, filed on Aug. 8, 2022, granted, now 11,900,515.
Application 17/883,555 is a continuation of application No. 17/499,772, filed on Oct. 12, 2021, granted, now 11,410,362.
Prior Publication US 2024/0212245 A1, Jun. 27, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G09G 5/00 (2006.01); G06T 11/20 (2006.01); G06T 11/60 (2006.01)
CPC G06T 11/60 (2013.01) [G06T 11/203 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing platform comprising:
a network interface;
at least one processor;
at least one non-transitory computer-readable medium; and
program instructions stored on the at least one non-transitory computer-readable medium that are executable by the at least one processor such that the computing platform is configured to:
receive a two-dimensional (2D) image file comprising a construction drawing; generate, using a first supervised image processing model, (i) a first set of polygons corresponding to respective areas of the 2D image file and (ii) a respective confidence score for each polygon in the first set of polygons;
generate, using a second supervised image processing model, (i) a second set of polygons corresponding to respective areas of the 2D image file and (ii) a respective confidence score for each polygon in the second set of polygons;
generate, using an unsupervised image processing model, (i) a third set of polygons corresponding to respective areas of the 2D image file and (ii) a respective confidence score for each polygon in the third set of polygons;
for each polygon from each set of polygons, determine a respective overlap with each polygon from the other sets of polygons;
based on (i) the determined overlap between polygons and (ii) the respective confidence scores for each of the overlapping polygons, determine a set of merged polygons corresponding to respective areas of the 2D image file; and
based on (i) the 2D image file and (ii) the set of merged polygons corresponding to the respective areas of the 2D image file, train one or both of the first supervised image processing model and the second supervised image processing model.