**Project Type: Box and bunlde counting
**Operating System & Browser: Windows/ Linux, Brave or Edge
**Project Universe Link or Workspace/Project ID: bundle-and-box
Hello to everyone, my name is Andres, Im a cs engineer, currently working on paperboard industry, I would like to know if anybody has worked with this type of task.
The goal is to count the boxes but on a more grained way, so the count is more precise, this is because at the moment they are counted by hand. The machine has an integrated counting sensor, so the idea is to compare both and be more efficient.
Im currently using keypoint detection but not sure if Im doing it correctly.
I’m not sure if keypoint detections is the right model for this task - from your explanation I understand the number of boxes may vary and with keypoints you most likely cannot have varying number, I might be wrong but my understanding is that keypoint model will try to fit all the keypoints.
I personally would try to train segmentation model to detect individual stacked boxes, or to detect the right edge and then try to count individual “waves” (but second option only if the camera is always taking photo from the same angle)
