Code Monkey home page Code Monkey logo

apollo-note's Introduction

Apollo 3.0阅读笔记

本文档主要介绍Apollo 3.0软件平台,其中各个模块结构与功能的纤细介绍。文档的目录结构为:

References:

apollo-note's People

Contributors

yannzyl avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

apollo-note's Issues

Model used

Which model is used for traffic light perception ?

Apollo-Note/docs/perception/obstacles_lidar_4_hmtrack.md ComputeAssociateMatrixhas issue for advice

Thank you very much for your summary and share.I would like to ask two questions in the Apollo/ Percetion/LIdar module:
The following source code, the path for "modules/perception/obstacle/lidar/tracker/hm_tracker/track_object_distance. cc" , when lidar track ComputeAssociateMatrixhas five factors, including: location_distance,direction_distance,bbox_size_distance,point_num_distance,histogram_distance. I want to ask whether there is any selection basis for selecting the 5 parameters for weighting. There are 5 default weights s_location_distance_weight_, s_direction_distance_weight_, s_bbox_size_distance_weight_, s_point_num_distance_weight_, s_histogram_distance_weight_ are where the selection is given**?
float TrackObjectDistance::ComputeDistance( ObjectTrackPtr track, const Eigen::VectorXf& track_predict, const std::shared_ptr<TrackedObject>& new_object) { // Compute distance for given trakc & object ....... float result_distance = s_location_distance_weight_ * location_distance + s_direction_distance_weight_ * direction_distance + s_bbox_size_distance_weight_ * bbox_size_distance + s_point_num_distance_weight_ * point_num_distance + s_histogram_distance_weight_ * histogram_distance; return result_distance; }

In the source code, association_(i, j) <= connected_threshold==4. What factors are considered in the selection of this connected_threshold=4?

Looking forward to your reply and best wishes!

关于分割后并查集聚类中的Traverse函数

@YannZyl 您好!非常感谢您的分享,学到很多。有一个问题问一下,在obstacles_lidar_2_cnn.md中分析的并查集部分中的Traverse函数,“每棵树只有一条path的is_center=true", 其他都是false,导致后续合并时一棵树只与另一棵树的指定支路去合并。” 不太明白为什么不把所有的path的is_center设为true,这样相近的所有树及分支都能够合并,只与一个path合并的话,不会漏掉与这一个path距离远而与其他path距离较近的同一个物体上的点吗?如果我想尝试合并所有相近的树和分支,是不是应该把if (x->traversed == 2)改为if(x->traversed == 2 || x->traversed == 1)?
谢谢!

如何在训练中标注中心offset数据

您好,看到在CNN网络的输出中,由两项数据是表示中心偏移,想请问,如果自己标注数据训练,这个中心偏移该如何标注呢?

HM

数据关联部分,在ConnectedComponentAnalysis中,得到的components二维向量中,每一行为一个子图的组成元素,这个子图是如何划分的,有点不明白

计算单元格的8个属性的问题

image
您好,我在看到计算单元格8个属性的代码时候,不是应该用映射之后的单元格吗?为什么又把坐标转到以激光雷达为中心,前后左右各60这里来了呢?我计算出来的center_x的范围是(-60,60),不是应该用width x height 上的单元格吗?麻烦您了

How to convert minbox direction center to quarterion?

Hi, may I ask how to convert the minbox direction and center into a Pose (with quarterion and dimension)?

Simply I know the l,w,h, means, but what does direction means? Coordinates terms to lidar origin? How to get the pose of obstacle in quarterion?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.