Methods and systems for automatic generation of massive training data sets from 3d models for training deep learning networks

A computer program product for generating training data sets for training deep learning networks for spatial feature extraction from two-dimensional (2D) images of a three-dimensional (3D) object, comprising a non-transitory computer readable storage medium having program instructions embodied therein, the program instructions executable by a processor to cause the processor to:

• receive a 3D model of the 3D object;
• extract spatial features from the 3D model;
• generate a first type of augmentation data for the 3D model;
• augment the 3D model with the first type of augmentation data to generate an augmented 3D model;
• generate at least one 2D image from the augmented 3D model by performing a projection of the augmented 3D model onto at least one plane;
• and
• generate a training data set to train the deep learning network (DLN) for spatial feature extraction by aggregating the spatial features and the at least one 2D image.

A system for generating training data sets for training deep learning networks for spatial feature extraction from two-dimensional (2D) images of a three-dimensional (3D) object, the system comprising:

• at least one processor;
• and
• at least one non-transitory computer readable storage medium having program instructions embodied therein, the program instructions executable by the at least one processor to cause the at least one processor to:
• receive a 3D model of the 3D object;
• extract spatial features from the 3D model;
• generate a first type of augmentation data for the 3D model;
• augment the 3D model with the first type of augmentation data to generate an augmented 3D model;
• generate at least one 2D image from the augmented 3D model by performing a projection of the augmented 3D model onto at least one plane;
• and
• generate a training data set to train the deep learning network (DLN) for spatial feature extraction by aggregating the spatial features and the at least one 2D image.