Skip to content
Pre-trained custom HOG detector for Cozmo cubes on greater distance
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

A pre-trained custom HOG (Histogram of Oriented Gradients) detector to detect Cozmo cubes on a greater distance than SDK is capable of.

The detector needs dlib installed, e.g.:

pip3 install --user dlib

Visualization of the pre-trained model (detector):


The displays Cozmo's video feed with bounding boxes for cubes. It does not detect which cube it is, only bounding boxes (if you look at Cozmo's feed the markers on the cubes indeed are too noisy at distance to be identified).

There is a faster HOG detector implementation that I'll be looking to implement in python, but even dlib is good enough with its ~200ms/image on a reasonably performant computer. Another improvement could be done by employing cubes' lights and some simple opencv functions.

You can’t perform that action at this time.