Reusable bag recognition
Described herein is a system that uses artificial intelligence to classify bags at a checkout station. The system includes a camera that captures an image of a bag during a transaction at a checkout station, a memory, and a processor communicatively coupled to the memory. The processor analyzes, using a machine learning model, the image of the bag to determine a characteristic of the bag; determines, using the machine learning model and based on the characteristic of the bag, that the bag is new; and adds the bag to the transaction in response to determining that the bag is new.
1 . A system comprising:
a camera arranged to capture an image of a bag during a transaction at a checkout station;
a memory; and
a processor communicatively coupled to the memory, the processor configured to:
analyze, using a machine learning model, the image of the bag to determine a characteristic of the bag;
determine, using the machine learning model and based on the characteristic of the bag, that the bag is new; and
add the bag to the transaction in response to determining that the bag is new.
2 . The system of claim 1 , wherein the characteristic comprises whether the bag has a frayed edge.
3 . The system of claim 1 , wherein the characteristic comprises whether the bag is discolored.
4 . The system of claim 1 , wherein the characteristic comprises whether a label is attached to the bag.
5 . The system of claim 1 , wherein the characteristic comprises a shape of the bag.
6 . The system of claim 1 , wherein the processor is further configured to determine a number of bags in the transaction that are the same as the bag, and wherein determining that the bag is new is further based on the number of bags.
7 . The system of claim 1 , wherein determining that the bag is new is further based on an inventory of bags.
8 . The system of claim 1 , wherein the processor is further configured to present a message based on determining that the bag is new.
9 . A method comprising:
capturing, by a camera, an image of a bag during a transaction at a checkout station;
analyzing, by a processor and using a machine learning model, the image of the bag to determine a characteristic of the bag;
determining, by the processor, using the machine learning model, and based on the characteristic of the bag, that the bag is new; and
adding the bag to the transaction in response to determining that the bag is new.
10 . The method of claim 9 , wherein the characteristic comprises whether the bag has a frayed edge.
11 . The method of claim 9 , wherein the characteristic comprises whether the bag is discolored.
12 . The method of claim 9 , wherein the characteristic comprises whether a label is attached to the bag.
13 . The method of claim 9 , wherein the characteristic comprises a shape of the bag.
14 . The method of claim 9 , further comprising determining a number of bags in the transaction that are the same as the bag, and wherein determining that the bag is new is further based on the number of bags.
15 . The method of claim 9 , wherein determining that the bag is new is further based on an inventory of bags.
16 . The method of claim 9 , further comprising presenting a message based on determining that the bag is new.
17 . A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to:
receive an image of a bag captured by a camera during a transaction at a checkout station;
analyze, using a machine learning model, the image of the bag to determine a characteristic of the bag;
determine, using the machine learning model and based on the characteristic of the bag, that the bag is new; and
add the bag to the transaction in response to determining that the bag is new.
18 . The medium of claim 17 , wherein the characteristic comprises whether the bag has a frayed edge.
19 . The medium of claim 17 , wherein the characteristic comprises whether the bag is discolored.
20 . The medium of claim 17 , wherein the characteristic comprises whether a label is attached to the bag.