Methods and apparatus for automatically defining computer-aided design files using machine learning, image analytics, and/or computer vision

An apparatus, comprising:

• a memory;
• and
• at least one processor operatively coupled to the memory, the at least one processor configured to receive data associated with a site of interest, the data including data representing a plurality of non-binary categories based on a set of characteristics of the site of interest and aerial data of the site of interest, the aerial data having a plurality of points arranged in a pattern,
• the at least one processor configured to execute a machine learning model to classify each point from the plurality of points into a set of non-binary categories from the plurality of non-binary categories, the at least one processor configured to select, for each point from the plurality of points, a category from the set of non-binary categories for that point based on a predefined category hierarchy,
• the at least one processor configured to, for each point from the plurality of points, identify a set of adjacent points from the plurality of points having a common category from the plurality of non-binary categories to define a shape from a plurality of shapes,
• the at least one processor configured to generate a file including at least one of a two-dimensional (2D) model or a three-dimensional (3D) model of aerial data using each shape from the plurality of shapes.

A method, comprising:

• receiving, via at least one processor, data associated with a site of interest, the data including data representing a plurality of non-binary categories associated with the site of interest and aerial data of the site of interest, the aerial data having a plurality of points arranged in a pattern;
• classifying, based at least in part on the at least one processor executing a machine learning model, each point from the plurality of points into a category from the plurality of non-binary categories;
• identifying, via the at least one processor and for each point from the plurality of points, a set of adjacent points from the plurality of points having a common category from the plurality of non-binary categories to define a shape from a plurality of shapes;
• defining, via the at least one processor, a polyline boundary of each shape from the plurality of shapes by analyzing with respect to a criterion a position of each point associated with a border of that shape relative to a position of at least one other point associated with the border of that shape;
• assigning, via the at least one processor, each shape from the plurality of shapes to a layer associated with the category from the plurality of non-binary categories for that shape from the plurality of shapes;
• and
• generating a file including at least one of a two-dimensional (2D) model or a three-dimensional (3D) model of aerial data using the polyline boundary of each shape from the plurality of shapes and the layer for each category from the plurality of non-binary categories.