This module runs a Darknet network and shows the top-scoring results. The network is currently a bit slow, hence it is only run once in a while. Point your camera towards some interesting object, make the object fit in the picture shown at right (which will be fed to the neural network), keep it stable, and wait for Darknet to tell you what it found.
Note that by default this module runs the Imagenet1k tiny Darknet (it can also run the slightly slower but a bit more accurate Darknet Reference network; see parameters). There are 1000 different kinds of objects (object classes) that this network can recognize (too long to list here).
Sometimes it will make mistakes! The performance of darknet-tiny is about 58.7% correct (mean average precision) on the test set, and Draknet Reference is about 61.1% correct on the test set.
On every frame where detection results were obtained, this module sends a message
where framenum is the frame number (starts at 0).
In addition, when detections are found which are avove threhsold, up to top messages will be sent, for those category candidates that have scored above thresh:
DKR category score
where category is the category name (from namefile) and score is the confidence scove from 0.0 to 100.0