Deep learning has revolutionized computer vision. There are thousands of Python code snippets to start but few ones in C++. If you like C++ like me and want to deploy your models in edge, then this series of posts are for you. As a gentle introduction, I will explain how to use libtorch to do […]

Raspberry Pi boards are getting more and more widespread. But when it comes to real-time video streaming, you may find yourself lost in a bunch of long-reptile shell commands! In this post, I will give you some crystal clear instructions to receive a low-latency stream from a CSI or USB camera. They key to achieve […]

In the previous post, I explained the idea behind cascade classifiers. In this post, I will give you some clear instructions to easily train an accurate custom object detector using my C++ toolbox. We will see how easily we can accelerate this accurate detector by 20%. Stay tuned :)

Cascade classifier is an old algorithm which was originally proposed for real-time face detection on CPUs. In this post, I will cover it’s nice and powerful idea, and then in the next post give you some clear instructions to easily train an accurate custom object detector using my C++ toolbox.

Multicore processing was a paradigm shift in computer science. The move was such big that today its really hard to find single-core CPUs even on low power SBCs. Computer vision algorithms, from simple pixel manipulations to the more complex tasks like classification with deep neural networks, have the potential to run parallel on multi cores. […]

Single Instruction Multiple Data (SIMD), also known as vectorization, is a powerful technique for accelerating computer vision algorithms. In this post, I will explain the concept and then introduce an easy way to use it inside your codes. We will see how we can benefit from SIMD to further reduce the runtime of the Gaussian-blur […]

The future of computer vision and machine learning is toward edge devices. This is why C++ matters. Following my previous post on simple and general tips to optimize C++ codes, I decided to explain further tips that are specified for implementing computer vision algorithms.

The first time I heard its name was 3 years ago in a robotic course. It seemed to be a big complex stuff for me which I tried to escape as much as I could. Soon after building the first ROS application, my interest increased in such a way that I like to ROS-ify almost […]

QR codes can store different types of data. Recently, I was involved in a project that a robot had to detect and decode pre-installed QR codes to refine its position. This post explains how I got 10 FPS performance on a Raspberry Pi Zero.

My master thesis was to design and implement a camera-based system for localization of a six-wheeled robot. The computer was a Raspberry Pi 3 which took me a lot of effort to achieve a reasonable performance. This post explains how I got 8-10 FPS localization on KITTI dataset.