Authors: WU Jia, GAO Jinwei NPU, short for neural processing unit, is a specialized processor designed to accelerate the performance of common machine learning tasks and typically of neural networks applications. Besides acceleration, NPU frees the CPU and it is pretty power efficient. OpenCV’s Dynamic Neural Network (DNN) module is a light and efficient deep […]
How to use OpenCV with OpenVINO
Guest post by Aleksandr Voron To keep OpenVINO™ Toolkit focused on optimizing and deploying inference, we no longer include OpenCV and DL Streamer in our distribution packages. But not to worry! Both OpenCV and DL Streamer continue to work with OpenVINO and in this blog post we will explain how. In the 2022.1 release of OpenVINO™, OpenCV became an optional […]
OpenCV Face Detection: Cascade Classifier vs. YuNet
Written by CHEN Zhangjie (Junior, Department of Computer Science and Engineering) Face Detection is a computer vision task in which a computer program detects the presence of human faces and also finds their locations in an image or a video stream. The technology has been rapidly advancing and maturing with various models being developed. The […]
Using the new highgui 3D visualization features
Features of highgui module with the addition of the viz3d namespace
Face recognition on Android using OpenVINO Toolkit with ARM plugin
Some time ago the article “How to create an application on x86 Android with OpenVINO” has been posted. However, most Android devices use ARM-based chips, so we decided to port the instruction to this platform. OpenVINO supports DL network inference on ARM platforms via ARM plugin, so there is no technical limitations to infer networks […]
OpenCV-Python for Apple’s M1 Chip: A Detective Story With A Happy Ending
Until recently OpenCV Python packages were provided for Windows, Linux (x86_64 and ARM), and macOS (formerly known as OSX) for x86_64 and all was right with the world. However, in November 2020, Apple launched its M1 processor and a series of new hardware based on it followed which changed the game- macOS now needs not […]
Recognizing one-dimensional barcode using OpenCV
Undergraduates Southern University of Science and Technology contributed the 1-D barcode recognition algorithm to opencv_contrib. In this blog post, they are introducing the algorithm and telling how to use it.
How to Train and Deploy Custom Models to OAK with Roboflow
In computer vision, there are number of general, pretrained models available for deployment to edge devices (such as OpenCV AI Kit). However, the real power in computer vision deployment today lies in custom training your own computer vision model on your own data to apply to your custom solution on your own device. To train […]
In Living Color (or Not)
Computer vision engineers often face a hard choice when settling on a sensor module: color or grayscale?
Optimizing OpenCV for the RISC-V Architecture
This post is the part of the Google Summer of Code 2020 project OpenCV runs on many hardware platforms and makes use of the SIMD (Single Instruction Multiple Data) acceleration on the ones that support it. Today we will describe how OpenCV was ported and accelerated for RISC-V. What is RISC-V and Why RISC-V From […]
Working with Orbbec Astra 3D cameras using OpenCV
How to work with 3D cameras in OpenCV. Illustrated by the example of Orbbec Astra
OpenVINO model optimization
Are you looking for a fast way to run neural network inferences on Intel platforms? Then OpenVINO toolkit is exactly what you need. It provides a large number of optimizations that allow blazingly fast inference on CPUs, VPUs, integrated graphics, and FPGAs. In the previous post, we’ve learned how to prepare and run DNN models […]
