Systems and methods for generating synthetic images of a training database

A system for training an image analysis system, the system comprising:

• a processor;
• and
• a nontransitory computer-readable medium including instructions that are executable by the processor, wherein the instructions include:
• generating one or more nominal images of at least a portion of a digital twin of an environment, wherein the digital twin is a virtual representation of the environment, and wherein the one or more nominal images are based on a field of view of an image sensor of the digital twin and one or more nominal characteristics of one or more components of the digital twin;
• defining one or more adjusted field of views of the image sensor;
• generating one or more auxiliary nominal images of at least the portion of the digital twin of the environment based on the one or more adjusted field of views and the one or more nominal characteristics;
• defining one or more anomalous characteristics of the one or more components;
• generating one or more anomalous images of the portion of the digital twin of the environment based on the field of view and one or more anomalous characteristics of the one or more components;
• generating one or more auxiliary anomalous images of the portion of the digital twin of the environment based on the one or more adjusted field of views and the one or more anomalous characteristics;
• performing a tessellation routine and a texture mapping routine on the one or more nominal images, the one or more auxiliary nominal images, the one or more anomalous images, and the one or more auxiliary anomalous images to generate a plurality of synthetic images;
• and
• labeling, for each synthetic image from among the plurality of synthetic images, the synthetic image as one of an anomalous type, a nominal type, or a combination thereof.

A method comprising:

• generating one or more nominal images of at least a portion of a digital twin of an environment, wherein the digital twin is a virtual representation of the environment, wherein the one or more nominal images are based on a field of view of an image sensor of the digital twin and one or more nominal characteristics of one or more components of the digital twin, and wherein the field of view is based on a nominal position coordinate of the image sensor and a nominal orientation of the image sensor;
• defining one or more adjusted field of views of the image sensor;
• generating one or more auxiliary nominal images of the portion of the digital twin of the environment based on the one or more adjusted field of views and the one or more nominal characteristics, wherein the one or more adjusted field of views are based on an adjusted position coordinate of the image sensor, an adjusted orientation of the image sensor, or a combination thereof;
• defining one or more anomalous characteristics of the one or more components;
• generating one or more anomalous images of the portion of the digital twin of the environment based on the field of view and one or more anomalous characteristics of the one or more components;
• generating one or more auxiliary anomalous images of the portion of the digital twin of the environment based on the one or more adjusted field of views and the one or more anomalous characteristics;
• performing a tessellation routine and a texture mapping routine on the one or more nominal images, the one or more auxiliary nominal images, the one or more anomalous images, and the one or more auxiliary anomalous images to generate a plurality of synthetic images;
• and
• labeling, for each synthetic image from among the plurality of synthetic images, the synthetic image as one of an anomalous type, a nominal type, or a combination thereof.