fengyuentau

Compiling OpenCV with TIM-VX Backend

We are thrilled to introduce you the TIM-VX backend integrated in OpenCV DNN, which allows OpenCV DNN runs quantized DL models in neural processing units (NPU) on edge devices, such as Khadas VIM3 etc. It achives up to 2X faster than ARM CPU backend for running face detection and recognition model from OpenCV Zoo. More details can be found in OpenCV Zoo Benchmarks.

TIM-VX is provided with x86_64 simulator. So you can try OpenCV with TIM-VX backend on your x86_64 machine following steps below, or if you happen to have a physical board equiped with the A311D chip (like the Khadas VIM3 mentioned above). In this guide, we provide two ways compiling OpenCV with TIM-VX backend:

• (Recommanded) Compile OpenCV together with TIM-VX.
• Compile OpenCV with TIM-VX library installed previously.

Requirem

zihaomu

Loop closure algorithm based on HF-Net for depth fusion

Student: Zihao Mu

Mentor: Rostislav Vasilikhin

Link to accomplished work:

• Merged PR: opencv_contrib/pull/3002;

mbinna

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

Akagi201

关于H264, 通用的5个进阶文档为

• [H.264_MPEG-4 Part 10 White Paper]
• [Video coding using the H.264 MPEG-4 AVC compression standard]
• [H.264 and MPEG-4 video compression]
• [Overview of the H.264_AVC Video Coding Standard]
• [Overview and Introduction to the Fidelity Range Extensions]

分三个阶段学习