This module finds objects by matching keypoint descriptors between the current image and a set of training images. Here we use SURF keypoints and descriptors as provided by OpenCV. The algorithm is quite slow and consists of 3 phases: detect keypoint locations, compute keypoint descriptors, and match descriptors from current image to training image descriptors. Here, we alternate between computing keypoints and descriptors on one frame (or more, depending on how slow that gets), and doing the matching on the next frame. This module also provides an example of letting some computation happen even after we exit the process() function. Here, we keep detecting keypoints and computing descriptors even outside process(). The itsKPfut future is our handle to that thread, and we also use it to alternate between detection and matching on alternating frames.
Simply add images of the objects you want to detect in JEVOIS:/modules/JeVois/ObjectDetect/images/ on your JeVois microSD card. Those will be processed when the module starts. The names of recognized objects returned by this module are simply the file names of the pictures you have added in that directory. No additional trainign procedure is needed. Beware that the more images you add, the slower the algorithm will run, and the higher your chances of confusions among several of your objects.