Automatic image selection for online product catalogs

A system comprising:

• one or more computer processors;
• and
• one or more computer-readable mediums storing instructions that, when executed by the one or more computer processors, cause the system to perform operations comprising:
• gathering a first set of feature data for a first image of a first item, the first set of feature data including image features describing the first image;
• determining a first probability score for the first image by using the first set of feature data as input in a machine learning model, the first probability score indicating an estimated probability that the first image is suitable to represent the first item, the machine learning model having been trained to predict an image for a listing of an online marketplace based on a set of training images of the first item and sets of feature data associated with the set of training images;
• gathering a second set of feature data for a second image of the first item, the second set of feature data including image features describing the second image;
• determining a second probability score for the second image by using the second set of feature data as input in the machine learning model, the second probability score indicating an estimated probability that the second image is suitable to represent the first item;
• and
• selecting, based on a comparison of at least the first probability score and the second probability score, the first image to represent the first item.

A non-transitory computer-readable medium storing instructions that, when executed by one or more computer processors of one or more computing devices, cause the one or more computing devices to perform operations comprising:

• gathering a first set of feature data for a first image of a first item, the first set of feature data including image features describing the first image;
• determining a first probability score for the first image by using the first set of feature data as input in a machine learning model, the first probability score indicating an estimated probability that the first image is suitable to represent the first item, the machine learning model having been trained to predict an image for a listing of an online marketplace based on a set of training images of the first item and sets of feature data associated with the set of training images;
• gathering a second set of feature data for a second image of the first item, the second set of feature data including image features describing the second image;
• determining a second probability score for the second image by using the second set of feature data as input in the machine learning model, the second probability score indicating an estimated probability that the second image is suitable to represent the first item;
• and
• selecting, based on a comparison of at least the first probability score and the second probability score, the first image to represent the first item.