US 12,001,512 B2 · Generating labeled synthetic training data

Abstract

Implementations are described herein for automatically labeling synthetic plant parts in synthetic training images, where the synthetic training images and corresponding labels can be used as training data for training machine learning models to detect, segment, and/or classify various parts of plants in digital images. In various implementations, a digital image may be obtained that captures an area. The synthetic training image may be generated to depict one or more three-dimensional synthetic plants in the area. In many implementations, a plant mask, identifying individual plants as a whole in the synthetic training image, as well as a part mask, uniquely identifying one or more parts of the synthetic plant models, can be overlaid on the synthetic training image to label the one or more parts of the synthetic plant models.

Claims20

Dependent claims

A method of generating a labeled synthetic training image, the method implemented by one or more processors and comprising:

generating one or more synthetic plant models, where each synthetic plant model includes (a) a textured portion of the synthetic plant model and (b) a segmented portion of the synthetic plant model uniquely identifying individual parts of the synthetic plant;
generating the synthetic training image based on (a) one or more texture portions of the one or more synthetic plant models and based on (b) a digital image that captures or synthesizes an area;
and
labeling the synthetic training image based on one or more of the segmented portions of the one or more synthetic plant models.

1 more element

Dependencies are inferred from the claim text.

Generating labeled synthetic training data

Life of this patent

Generating labeled synthetic training data

Life of this patent

Abstract

Claims20