Accelerating the performance of the object detection project

We approached accelerating the Computer Vision project in three key steps:

1. We moved computation from CPU to GPU.
2. We optimized the mixing of blurred and the original image
3. We switched the Gaussian filter to the Box Filter.

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.

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