Deep Learning in detection and classification of any LEGO elements by Enigma Pattern

Some details

Project description:

Enigma Pattern has created a new type of Deep Neural Network that allows real time detection and classification of LEGO items out of 400.000 different LEGO elements. For training it requires only synthetic images.

Challenges:

Lack of real pictures of LEGO elements taken in different lighting conditions reflecting possible scenarios of children’s play. 

Technologies and methods used:

TensorFlow, TensorFlow Lite, CoreML, Unity 3D, our proprietary “Synthesis” method 

Results: mAP 89%, real time detection and classification experience