  Pistachios are nutritious nuts that are sorted based on the shape of their
shell into two categories: Open-mouth and Closed-mouth. The open-mouth
pistachios are higher in price, value, and demand than the closed-mouth
pistachios. Because of these differences, it is considerable for production
companies to precisely count the number of each kind. This paper aims to
propose a new system for counting the different types of pistachios with
computer vision. We have introduced and shared a new dataset of pistachios,
including six videos with a total length of 167 seconds and 3927 labeled
pistachios. Unlike many other works, our model counts pistachios in videos, not
images. Counting objects in videos need assigning each object between the video
frames so that each object be counted once. The main two challenges in our work
are the existence of pistachios' occlusion and deformation of pistachios in
different frames because open-mouth pistachios that move and roll on the
transportation line may appear as closed-mouth in some frames and open-mouth in
other frames. Our novel model first is trained on the RetinaNet object detector
network using our dataset to detect different types of pistachios in video
frames. After gathering the detections, we apply them to a new counter
algorithm based on a new tracker to assign pistachios in consecutive frames
with high accuracy. Our model is able to assign pistachios that turn and change
their appearance (e.g., open-mouth pistachios that look closed-mouth) to each
other so does not count them incorrectly. Our algorithm performs very fast and
achieves good counting results. The computed accuracy of our algorithm on six
videos (9486 frames) is 94.75%.
