Gasket part selection via image processing

A computer-implemented method comprising:

• receiving a cross-section image of a gasket, the gasket having one or more defects;
• generating, a feature representation of the cross-section image of the gasket using a machine learning model;
• and
• identifying, using the machine learning model, a replacement gasket from a dataset including gasket profiles and a deformation compensation.

A computer-implemented method for training a machine learning model, the method comprising:

• receiving a training dataset, the training dataset including cross-section image of a gasket having one or more defects, and a ground truth cross-section image of the gasket without defects;
• generating, using the machine learning model, a modified feature representation based on the cross-section image of the gasket and a deformation compensation;
• generating, using the machine learning model, a ground-truth feature representation based on the ground-truth cross-section image of the gasket from the training dataset;
• calculating a loss based on difference between the modified feature representation and the ground-truth feature representation;
• and
• updating parameters of the machine learning model based on the loss.