CPC G06F 18/214 (2023.01) [G06F 18/2431 (2023.01); G06T 15/04 (2013.01); G06T 17/20 (2013.01); G06V 20/10 (2022.01)] | 20 Claims |
1. A method for training an image analysis system 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, 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 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 the one or more anomalous characteristics;
performing a tessellation routine and a texture mapping routine on the one or more nominal images and the one or more 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.
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