Systems and methods for item identification

A method for transaction completion, the method comprising:

• receiving, at an item staging area, one or more items to be included in a transaction at a facility;
• capturing, by an optical scanner, a machine-readable code of an item of the one or more items to identify the item;
• capturing, by a camera of a computer vision system having a lens, an image of the item when a presence of the item is detected;
• determining, by a trained machine learning model when executed by a control circuit of the computer vision system, whether the machine-readable code of the item is received by the control circuit;
• identifying, by the trained machine learning model when executed by the control circuit, the item based on the image captured by the camera;
• upon a determination that the machine-readable code of the item is received and upon a determination that the machine-readable code and the image do not correspond to a same item, automatically updating, by the trained machine learning model when executed by the control circuit, content shown in a display to identify the item based on the image;
• upon a determination that the machine-readable code is not received and the trained machine learning model is able to determine an item sub-category corresponding to the item based on the image but unable to identify the item:
• automatically updating, by the trained machine learning model when executed by the control circuit, content shown in the display to provide at least two items similar to the item with a prompt for a user selection of the item intended for purchase;
• and
• automatically updating, by the trained machine learning model when executed by the control circuit, the trained machine learning model;
• upon a determination that the machine-readable code is not received and the trained machine learning model is able to determine an item category corresponding to the item based on the image but unable to identify the item, automatically updating, by the trained machine learning model when executed by the control circuit, the content shown in the display to provide a prompt to scan the item with the optical scanner;
• and
• upon a determination that the machine-readable code is not received and the trained machine learning model is unable to identify the item, but the item has been indicated by a user that the item has been presented for purchase, automatically updating, by the trained machine learning model when executed by the control circuit, the content shown in the display to provide a prompt to scan the item with the optical scanner.

A non-transitory machine-readable medium storing instructions executable by a control circuit of a computer vision system executing a trained machine learning model, the non-transitory machine-readable medium comprising:

• instructions to determine whether a machine-readable code of an item captured by an optical scanner is received by the control circuit, wherein the item is received at an item staging area of a facility;
• instructions to identify the item based on an image captured by a camera of the computer vision system;
• instructions to automatically update content shown in a display to identify the item based on the image upon determining that the machine-readable code of the item is received and upon determining that the machine-readable code and the image do not correspond to a same item;
• instructions to automatically update content shown in a display to provide at least two items similar to the item with a prompt for a user selection of the item intended for purchase upon determining that the machine-readable code is not received and the trained machine learning model is able to determine an item sub-category corresponding to the item based on the image but unable to identify the item;
• instructions to automatically update the trained machine learning model in response to the user selection;
• and
• instructions to automatically update the content shown in a display to provide a prompt to scan the item with the optical scanner upon determining that the machine-readable code is not received and the trained machine learning model is able to determine an item category corresponding to the item based on the image but unable to identify the item;
• and
• instructions to automatically update the content shown in the display to provide a prompt to scan the item with the optical scanner upon determining that the machine-readable code is not received, and the trained machine learning model is unable to identify the item, but the item has been indicated by a user that the item has been presented for purchase.