Abstract: A part machining feature recognition method based on machine vision learning recognition comprises sample training and part machining feature recognition. The sample training specifically refers to obtaining the 2D images of different 3D models of parts at different angles, marking machining feature information, constructing a 2D image sample, and then performing feature recognition training on the image recognition model using the 2D image samples; the part machining feature recognition specifically refers to taking 2D image screenshots from multiple view angles, recognizing all machining features from 2D image screenshots using the trained image recognition model, mapping the recognized machining features to the 3D model of parts with machining features to be recognized based on the view angle relationship, marking the machining features and geometric surfaces contained in each feature, and completing the automatic recognition of part machining features.

Abstract: A part machining feature recognition method based on machine vision learning recognition comprises sample training and part machining feature recognition. The sample training specifically refers to obtaining the 2D images of different 3D models of parts at different angles, marking machining feature information, constructing a 2D image sample, and then performing feature recognition training on the image recognition model using the 2D image samples; the part machining feature recognition specifically refers to taking 2D image screenshots from multiple view angles, recognizing all machining features from 2D image screenshots using the trained image recognition model, mapping the recognized machining features to the 3D model of parts with machining features to be recognized based on the view angle relationship, marking the machining features and geometric surfaces contained in each feature, and completing the automatic recognition of part machining features.