This case study shows our project related to image processing and computer vision. The main goal was to achieve significant performance acceleration of existing solution.
Client is under strict NDA.
Our goal was to speed the application (more specifically the Mask R-CNN's inference) so that the processing of high-resolution photos would be faster and more efficient. At the same time, it was crucial not to deteriorate the application's capabilities.
We approached accelerating the Computer Vision project in three key steps:
Before our improvements, the application needed ~3 minutes to process one image, and the inference of a neural network occupied 70% of this time. After changes made by Flyps’ experts, the time it took for neural networks decreased to 9 seconds. Thanks to the applied changes, the application has been accelerated by 20 times.
Building advanced technology for cashierless shops. Creating software that allows to run autonomous stores with innovative solutions that simplify shopping and help achieve a natural take-away result.