Systems and methods for training machine models with augmented data

A system comprising one or more processors and non-transitory computer storage media storing instructions that when executed by the one or more processors, cause the processors to:

• obtain a plurality of images and associated training outputs, the images being captured by cameras of one or more vehicles;
• for an individual image of the plurality of images, generate an augmented image for the individual image based on modifying the individual image with an image manipulation function of one or more image manipulation functions which maintain camera properties of the individual image, such that angle, scale, and/or pose associated with the individual image is preserved, wherein the augmented training image is associated with the associated training output of the individual image, and
• wherein the one or more image manipulation functions include a cutout function which adjusts a portion of an image based on a region of interest, wherein the portion of the image partially overlaps with an object in the image, the cutout being a solid color and the cutout being blended with regions near the cutout;
• and
• train the predictive computer model based, at least, on the individual image and the augmented image, wherein the trained predictive computer model is configured to predict a presence of objects in input images for use in autonomous or semi-autonomous control of a particular vehicle.

A non-transitory computer-readable medium having instructions for execution by a processor, the instructions when executed by the processor causing the processor to:

• obtain a plurality of images and associated training outputs, the images being captured by cameras of one or more vehicles;
• for an individual image of the plurality of images, generate an augmented image for the individual image based on modifying the individual image with an image manipulation function of one or more image manipulation functions which maintain camera properties of the individual image, such that angle, scale, and/or pose associated with the individual image is preserved, wherein the augmented training image is associated with the associated training output of the individual image, and
• wherein the one or more image manipulation functions include a cutout function which adjusts a portion of an image based on a region of interest, wherein the image is obtained via a particular camera, and wherein the region of interest corresponds to artifacts which are always present in images obtained via the particular camera;
• and
• train the predictive computer model based, at least, on the individual image and the augmented image, wherein the trained predictive computer model is configured to predict a presence of objects in input images for use in autonomous or semi-autonomous control of a particular vehicle.