DB父子 vs. OO父子（技术）
引子 主键外键-父表子表再认识 一个联系信息的概念的分类例子： 用户的联系信息1 用户的目标对象(收货人)的联系信息2 厂商的联系信息1 经销商的联系信息1 经销商店铺联系信息2 由以上的信息可得，联系信息需求分为两大类： 与业务实体成一对一关系的，联系信
引子
主键外键-父表子表再认识
一个联系信息的概念的分类例子：
• 用户的联系信息1
• 用户的目标对象(收货人)的联系信息2
• 厂商的联系信息1
• 经销商的联系信息1
• 经销商店铺联系信息2
由以上的信息可得，联系信息需求分为两大类：
- 与业务实体成一对一关系的，联系信息ID以外键关系置入业务对象的。如用户、厂商和经销商自身 的信息；
- 用户、厂商和经销商等业务对象所需要的与他有业务关系多个联系人信息。用户的收货人信息和经 销商的店铺的联系信息。
分析
我的联系信息是我的个人属性，它竟然是我的“父”？对吗?
很明显，关系数据库里的父子关系概念与OO的父子类概念是不一样的。
很有趣的是，关系数据库集中关注的是对象间的横向“关系”，几乎没有纵向关系的表达；而OO则相反，继承多态都是纵向关系的表达。当然横向关系也可以表 达，好像表达得不太自然。
因此，关系数据库的“父子”不等于OO的“父子”。
横向“关系”的父是更基本的元素，元素粒度越小，元素越“长”越“老”。关系系数为一，只有主键；
横向“关系”的子是二次元素，元素内有父元素的组成部分；关系系数为多。一定有外键。
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1393
52
1205
24
Have you really mastered coordinate system conversion? Multi-sensor issues that are inseparable from autonomous driving
Oct 12, 2023 am 11:21 AM
The first pilot and key article mainly introduces several commonly used coordinate systems in autonomous driving technology, and how to complete the correlation and conversion between them, and finally build a unified environment model. The focus here is to understand the conversion from vehicle to camera rigid body (external parameters), camera to image conversion (internal parameters), and image to pixel unit conversion. The conversion from 3D to 2D will have corresponding distortion, translation, etc. Key points: The vehicle coordinate system and the camera body coordinate system need to be rewritten: the plane coordinate system and the pixel coordinate system. Difficulty: image distortion must be considered. Both de-distortion and distortion addition are compensated on the image plane. 2. Introduction There are four vision systems in total. Coordinate system: pixel plane coordinate system (u, v), image coordinate system (x, y), camera coordinate system () and world coordinate system (). There is a relationship between each coordinate system,
The Stable Diffusion 3 paper is finally released, and the architectural details are revealed. Will it help to reproduce Sora?
Mar 06, 2024 pm 05:34 PM
StableDiffusion3’s paper is finally here! This model was released two weeks ago and uses the same DiT (DiffusionTransformer) architecture as Sora. It caused quite a stir once it was released. Compared with the previous version, the quality of the images generated by StableDiffusion3 has been significantly improved. It now supports multi-theme prompts, and the text writing effect has also been improved, and garbled characters no longer appear. StabilityAI pointed out that StableDiffusion3 is a series of models with parameter sizes ranging from 800M to 8B. This parameter range means that the model can be run directly on many portable devices, significantly reducing the use of AI
This article is enough for you to read about autonomous driving and trajectory prediction!
Feb 28, 2024 pm 07:20 PM
Trajectory prediction plays an important role in autonomous driving. Autonomous driving trajectory prediction refers to predicting the future driving trajectory of the vehicle by analyzing various data during the vehicle's driving process. As the core module of autonomous driving, the quality of trajectory prediction is crucial to downstream planning control. The trajectory prediction task has a rich technology stack and requires familiarity with autonomous driving dynamic/static perception, high-precision maps, lane lines, neural network architecture (CNN&GNN&Transformer) skills, etc. It is very difficult to get started! Many fans hope to get started with trajectory prediction as soon as possible and avoid pitfalls. Today I will take stock of some common problems and introductory learning methods for trajectory prediction! Introductory related knowledge 1. Are the preview papers in order? A: Look at the survey first, p
DualBEV: significantly surpassing BEVFormer and BEVDet4D, open the book!
Mar 21, 2024 pm 05:21 PM
This paper explores the problem of accurately detecting objects from different viewing angles (such as perspective and bird's-eye view) in autonomous driving, especially how to effectively transform features from perspective (PV) to bird's-eye view (BEV) space. Transformation is implemented via the Visual Transformation (VT) module. Existing methods are broadly divided into two strategies: 2D to 3D and 3D to 2D conversion. 2D-to-3D methods improve dense 2D features by predicting depth probabilities, but the inherent uncertainty of depth predictions, especially in distant regions, may introduce inaccuracies. While 3D to 2D methods usually use 3D queries to sample 2D features and learn the attention weights of the correspondence between 3D and 2D features through a Transformer, which increases the computational and deployment time.
The first multi-view autonomous driving scene video generation world model | DrivingDiffusion: New ideas for BEV data and simulation
Oct 23, 2023 am 11:13 AM
Some of the author’s personal thoughts In the field of autonomous driving, with the development of BEV-based sub-tasks/end-to-end solutions, high-quality multi-view training data and corresponding simulation scene construction have become increasingly important. In response to the pain points of current tasks, "high quality" can be decoupled into three aspects: long-tail scenarios in different dimensions: such as close-range vehicles in obstacle data and precise heading angles during car cutting, as well as lane line data. Scenes such as curves with different curvatures or ramps/mergings/mergings that are difficult to capture. These often rely on large amounts of data collection and complex data mining strategies, which are costly. 3D true value - highly consistent image: Current BEV data acquisition is often affected by errors in sensor installation/calibration, high-precision maps and the reconstruction algorithm itself. this led me to
GSLAM | A general SLAM architecture and benchmark
Oct 20, 2023 am 11:37 AM
Suddenly discovered a 19-year-old paper GSLAM: A General SLAM Framework and Benchmark open source code: https://github.com/zdzhaoyong/GSLAM Go directly to the full text and feel the quality of this work ~ 1 Abstract SLAM technology has achieved many successes recently and attracted many attracted the attention of high-tech companies. However, how to effectively perform benchmarks on speed, robustness, and portability with interfaces to existing or emerging algorithms remains a problem. In this paper, a new SLAM platform called GSLAM is proposed, which not only provides evaluation capabilities but also provides researchers with a useful way to quickly develop their own SLAM systems.
How to set the return key and home key on Redmi K70Pro?
Feb 23, 2024 pm 01:40 PM
Mobile phones are now a necessity for young and middle-aged people. Of course, people of each age group have different needs for mobile phones. As one of the more popular models now, RedmiK70Pro has a very diverse range of functions and services that can meet the needs of consumers of different ages. How to set the return key and home key on Redmi K70Pro? You also need to understand it clearly. Only after you understand it can you decide whether to buy this mobile phone. Then follow the editor to take a look at the following content! How to set the return key and home key on Redmi K70Pro? To access your phone's settings menu, you can open the settings interface by pulling down the notification shade or looking for the settings icon on your home screen. In the settings interface, find and click "Button" or "Navigation Bar"
'Minecraft' turns into an AI town, and NPC residents role-play like real people
Jan 02, 2024 pm 06:25 PM
Please note that this square man is frowning, thinking about the identities of the "uninvited guests" in front of him. It turned out that she was in a dangerous situation, and once she realized this, she quickly began a mental search to find a strategy to solve the problem. Ultimately, she decided to flee the scene and then seek help as quickly as possible and take immediate action. At the same time, the person on the opposite side was thinking the same thing as her... There was such a scene in "Minecraft" where all the characters were controlled by artificial intelligence. Each of them has a unique identity setting. For example, the girl mentioned before is a 17-year-old but smart and brave courier. They have the ability to remember and think, and live like humans in this small town set in Minecraft. What drives them is a brand new,
