Given a collection of Blob objects (see Blob), the crossing detector module allows to apply a pre-computed model of the area to each of the blobs and, if specified, use a function approximator (in this case a convolutional neural network) in order to distinguish between Blob representing single individual and touching individuals.
crossing_detector.detect_crossings(list_of_blobs, video, model_area, use_network=True, return_store_objects=False, plot_flag=True)[source]