java源码蓝牙通讯蓝牙通信示例 该项目的唯一要求是使用蓝牙技术在计算机和 Android 设备之间进行通信。 一种通信方式仅 PC 客户端 → Android Serverq。 PC 客户端使用 BlueCove 框架来利用 Java 提供的可移植性。 此示例在OSX和 Android 设备 LG-P500 (Optimus One) 中进行了测试。 该代码被授权为MIT （如所有源代码文件中所示）。

CMake Protobuf 示例 使用 CMake 通过 protobuf 管理 C++ 项目的最小示例。 建造 $ mkdir build $ cd build $ cmake .. $ make 跑步 $ ./main

这本是是ROS by example vol 2.是在第一册的基础上进行的改版。

条纹示例 一个示例项目，学习如何将条带集成到应用程序

SELinux by example is the first complete, hands-on guide to using SELinux in production environments. Authored by three leading SELinux researchers and developers, it illuminates every facet of working with SELinux, from its architecture and security object model to its policy language. This book thoroughly explains SELinux sample policies including the powerful new Reference Policy showing how to quickly adapt them to your unique environment. It also contains a comprehensive SELinux policy language reference and covers exciting new features in Fedora Core 5 and the upcoming Red Hat Enterprise Linux version 5.

Build real-world computer vision applications and develop cool demos using OpenCV for Python, About This Book, Learn how to apply complex visual effects to images using geometric transformations and image filtersExtract features from an image and use them to develop advanced applicationsBuild algorithms to help you understand the image content and perform visual searches, Who This Book Is For, This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV-Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on., What You Will Learn, Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like imageDetect and track various body parts such as the face, nose, eyes, ears, and mouthStitch multiple images of a scene together to create a panoramic imageMake an object disappear from an imageIdentify different shapes, segment an image, and track an object in a live videoRecognize an object in an image and build a visual search engineReconstruct a 3D map from imagesBuild an augmented reality application, In Detail, Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we are getting more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Web developers can develop complex applications without having to reinvent the wheel., This book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off with applying geometric transformations to images. We then discuss affine and projective transformations and see how we can use them to apply cool geometric effects to photos. We will then cover techniques used for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications., This book will also provide clear examples written in Python to build OpenCV applications. The book starts off with simple beginner's level tasks such as basic processing and handling images, image mapping, and detecting images. It also covers popular OpenCV libraries with the help of examples., The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation., Style and approach, This is a conversational-style book filled with hands-on examples that are really easy to understand. Each topic is explained very clearly and is followed by a programmatic implementation so that the concept is solidified. Each topic contributes to something bigger in the following chapters, which helps you understand how to piece things together to build something big and complex.

本示例利用一些代码来制作基于3D CAD的聚变React堆模型，以用于OpenMC仿真。 该模型是具有反射面的90度扇形模型。 该基于CadQuery 2和用于制作3D模型 使用带有DAGMC插件的Trelis / Cubit将CAD模型转换为h5m文件 用来制作3D html图像 使用Jupyter-cadquery和Python进行添加的Jupyter实验室用于制作python笔记本文件。

linux下网络socket编程,经典老美教材

WebSocket示例 该项目是通过引导的。 服务器 该服务器是使用FastAPI实现的。 首先，安装依赖项： pip install fastapi "uvicorn[standard]" 然后，运行它： uvicorn run:app 必须在localhost:8000中创建服务器。 客户 客户端使用React和Recharts实现。 转到前端目录： cd frontend 安装依赖项： yarn install 并运行它： yarn start 在localhost:3000打开浏览器，您必须看到每秒更新一次的图表。

在使用VS编译 VTK 8.2.0 时顺手生成的VTK示例文件,大概有20余个吧,文件夹里已经包含依赖,可正常运行 VTK示例文件 VTK_Example