Automatic image cropping using generative artificial intelligence
AssigneeAdobe Inc.
InventorsAshish CHOPRA, Vangala Naveen REDDY
Life of this patent
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Abstract
Some aspects relate to technologies providing a framework for automatically cropping images. In accordance with some aspects, a list of objects that are present in at least on image of a set of images is generated and that list is combined with a list of desired objects obtained from a content brief. In some aspects, the items in this combined list is ranked and this ranked list is used to detect and rank regions within images of the set of images that correspond to the combined and ranked list. In some aspects, these detected and ranked regions are used to inform the image cropping.
Claims20
One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations, the operations comprising:
- obtaining a source image;
- obtaining a set of guidelines for cropping the source image;
- generating a list of objects present in the source image, using an object
- recognition model;
- generating a list of desired objects based, at least in part, on the set of guidelines for cropping the source image;
- combining the list of objects and the list of desired objects to generate a list of object keywords;
- identifying regions of the source image that contain at least one object of the list of objects based, at least in part, on the list of object keywords;
- and
- generating a cropped image from the source image, of a desired image size specified in the set of guidelines, wherein the cropped image at least includes a selected identified region of the identified regions.
A computer-implemented method comprising:
- generating, by an object detection component, a list of objects present in a digital asset selected from a set of digital assets;
- generating, by an object inference component, a list of desired objects based, at least in part, on a set of guidelines for cropping digital assets;
- combining, by the object inference component, the list of objects and the list of desired objects to generate a list of object keywords;
- assigning, by the object inference component, a ranking to each object keyword in the list of object keywords to generate a ranked list of object keywords;
- augmenting, by an object augmentation component, the ranked list of object keywords by removing object keywords from the ranked list of object keywords based, at least in part, on the ranking of the object keywords;
- identifying, by an object region detection and re-ranking component, regions of the selected digital asset that contain at least one object of the list of objects based, at least in part, on the ranked list of object keywords;
- and
- generating, by an image cropping component, a cropped version of the selected digital asset that at least includes a selected identified region of the identified regions.
A computer system comprising:
- one or more processors;
- and
- one or more computer storage media storing computer-useable instructions that,
- when used by the one or more processors, causes the computer system to perform operations comprising:
- generating, by an object detection component, a list of objects present in a at least one image of an image corpus;
- generating, by an object inference component, a list of desired objects based, at least in part, on a set of guidelines obtained from a content brief;
- combining, by the object inference component, the list of objects and the list of desired objects to generate a list of object keywords;
- assigning, by the object inference component, a ranking to each object keyword in the list of object keywords to generate a ranked list of object keywords;
- identifying, by an object region detection and re-ranking component, regions of a selected image of the image corpus that contain at least one object of the list of objects based, at least in part, on the ranked list of object keywords;
- and
- generating, by an image cropping component, a cropped version of the selected image that at least includes a selected identified region of the identified regions.
Dependencies are inferred from the claim text.