Co-located sensors in a sorting facility

A system, comprising:

• a first sensor associated with a first field of view, and wherein the first sensor is located in a sorting facility;
• a second sensor associated with a second field of view, wherein the second field of view is adjacent to or overlaps with the first field of view, and wherein the second sensor is located in the sorting facility, wherein a combination of the first field of view and the second field of view covers at least a width of a conveyor device;
• and
• one or more processors configured to:
• receive a first image including a first set of objects from the first sensor, wherein the first set of objects is located on the conveyor device;
• receive a second image including a second set of objects from the second sensor, wherein the second set of objects is located on the conveyor device;
• generate a master image by combining the first image and the second image, wherein the first image shows a target object with an occluded portion, wherein the occluded portion of the target object is visible within the master image;
• determine a set of attributes associated with the target object based at least in part on using a machine learning model to evaluate the master image, wherein the machine learning model has been trained on master images that have been stitched together from images captured by individual sensors;
• determine a sorting operation to be performed on the target object based at least in part on the set of attributes associated with the target object, wherein the sorting operation to be executed by a set of sorting devices that is located downstream from the first sensor and the second sensor in the sorting facility;
• obtain, by an audit sensor, a third image depicting an execution of the sorting operation on the target object to divert the target object towards a desired destination, wherein the audit sensor comprises a third sensor located downstream from the first sensor and the second sensor in the sorting facility;
• determine an audit result based on whether the sorting operation was successful or not based on the third image by programmatically determining whether the target object appears to be successfully directed towards the desired destination in the third image;
• determine a capture success rate associated with the set of sorting devices based at least in part on the audit result;
• and
• determine whether to retrain the machine learning model used to detect the set of attributes associated with the target object based at least in part on the capture success rate.