Patent ID: 11941816
Assignee: GRACENOTE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method carried out by a machine learning (ML) predictor program implemented on a computing device and configured for generating predicted cropping characteristics for input images, wherein cropping characteristics for any given input image comprise coordinates of cropping boundaries with respect to the any given input image prior to cropping, the method comprising:
receiving one or more uncropped images by the computing device;
applying the ML predictor program to the one or more uncropped images in order to generate for each respective uncropped image of the one or more uncropped images a respective set of runtime cropping characteristics, wherein the respective set of runtime cropping characteristics for each respective uncropped image comprises one or more subsets of cropping coordinates for the respective uncropped image, and wherein each subset corresponds to a different cropped version of the respective uncropped image; and
storing, in non-transitory computer-readable memory, the one or more uncropped images together with the respective set of runtime cropping characteristics for each respective uncropped image of the one or more uncropped images,
wherein, prior to receiving the one or more uncropped images, the ML predictor program has been trained to predict cropping characteristics for each respective training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a respective set of training master images associated with the respective training raw image,
and wherein each training master image of the respective set of training master images indicates respective cropping characteristics defined for the associated respective training raw image.