Method and system for generating a geometric component using machine learning models

A data processing system for generating a geometric component in a computer-aided design (CAD) environment, the data processing system comprising:

• a processing unit;
• and
• a memory unit communicatively coupled to the processing unit, wherein the memory unit comprises a component generation module configured to:
• determine a geometric operation to be performed on the geometric component in the CAD environment based on a CAD command selected by a user;
• determine one or more candidate groups, each candidate group of the one or more candidate groups comprising one or more candidates in the geometric component suitable for performing the geometric operation using one or more trained machine learning models, wherein the determination of the one or more candidate groups comprises generation of feature data associated with the geometric component, wherein the feature data comprises object feature data associated with the geometric component, prediction of a plurality of candidates associated with the geometric operation to be performed on the geometric component based on the generated feature data using the one or more trained machine learning models, and creation of the one or more candidate groups from the plurality of the candidates based on pre-defined grouping rules;
• identify at least one candidate group on which the geometric operation is to be performed from the one or more candidate groups;
• and
• perform the geometric operation on the one or more candidates in the identified at least one candidate group.

A non-transitory computer-readable storage medium that stores machine-readable instructions executable by a data processing system to generate a geometric component in a computer-aided design (CAD) environment, the machine-readable instructions comprising:

• determining a geometric operation to be performed on the geometric component in the CAD environment;
• determining one or more candidate groups, each of the one or more candidate groups comprising one or more candidates in the geometric component suitable for performing the geometric operation using one or more trained machine learning models, wherein determining the one or more candidate groups comprises generating feature data associated with the geometric component, wherein the feature data comprises object feature data associated with the geometric component, predicting a plurality of candidates associated with the geometric operation to be performed on the geometric component based on the generated feature data using the one or more trained machine learning models, and creating the one or more candidate groups from the plurality of the candidates based on pre-defined grouping rules;
• identifying at least one candidate group on which the geometric operation is to be performed from the one or more candidate groups;
• and
• performing the geometric operation on the one or more candidates in the identified at least one candidate group.