单目高程网络检测

功能介绍

elevation_net是基于hobot_dnn package开发的高程网络检测算法示例,在地平线的旭日X3派上使用高程网络模型和室内数据利用BPU进行模型推理,从而得到算法推理结果。

代码仓库:https://c-gitlab.horizon.ai/HHP/box/hobot_perception/elevation_net

应用场景:单目高程网络检测算法通过解析图片得到像素点的深度和高度信息,主要应用于自动驾驶、智能家居、智能交通等领域。

支持平台

平台 运行方式 示例功能
旭日X3派 Ubuntu 20.04 · 启动本地回灌,推理渲染结果保存在本地
X86 Ubuntu 20.04 · 启动本地回灌,推理渲染结果保存在本地

准备工作

旭日X3派

  1. 旭日X3派已烧录好地平线提供的Ubuntu 20.04系统镜像。

  2. 旭日X3派已成功安装TogetheROS.Bot。

X86平台

  1. X86环境已配置Ubuntu 20.04系统镜像。

  2. X86环境已成功安装tros.b。

使用介绍

单目高程网络检测算法示例package采用读取本地图片的形式,经过算法推理后检测出Image基于像素的深度和高度信息,同时package将深度和高度信息进行处理,发布PointCloud2话题数据,用户可以订阅PointCloud2数据用于应用开发。

旭日X3派

# 配置ROS2环境
source /opt/tros/setup.bash

# 从tros.b的安装路径中拷贝出运行示例需要的配置文件。
cp -r /opt/tros/lib/elevation_net/config/ .

# 启动launch文件
ros2 launch /opt/tros/share/elevation_net/launch/hobot_elevation_net.launch.py

X86平台

# 配置ROS2环境
source /opt/tros/setup.bash

# 从tros.b的安装路径中拷贝出运行示例需要的配置文件。
cp -r /opt/tros/lib/elevation_net/config/ .

# 启动launch文件
ros2 launch /opt/tros/share/elevation_net/launch/hobot_elevation_net.launch.py

结果分析

package在运行终端推理输出如下信息:

[16:15:17:520]root@ubuntu:/userdata# ros2 run elevation_net elevation_net
[16:15:18:976][WARN] [1655108119.406738772] [example]: This is dnn node example!
[16:15:19:056][WARN] [1655108119.475098438] [elevation_dection]: Parameter:
[16:15:19:056]config_file_path_:./config
[16:15:19:056] model_file_name_: ./config/elevation.hbm
[16:15:19:058]feed_image:./config/images/charging_base.png
[16:15:19:058][INFO] [1655108119.475257138] [dnn]: Node init.
[16:15:19:058][INFO] [1655108119.475309553] [elevation_dection]: Set node para.
[16:15:19:058][INFO] [1655108119.475370258] [dnn]: Model init.
[16:15:19:058][BPU_PLAT]BPU Platform Version(1.3.1)!
[16:15:19:095][HBRT] set log level as 0. version = 3.13.27
[16:15:19:095][DNN] Runtime version = 1.8.4_(3.13.27 HBRT)
[16:15:19:133][000:000] (model.cpp:244): Empty desc, model name: elevation, input branch:0, input name:inputquanti-_output
[16:15:19:133][000:000] (model.cpp:244): Empty desc, model name: elevation, input branch:1, input name:inputquanti2-_output
[16:15:19:134][000:000] (model.cpp:313): Empty desc, model name: elevation, output branch:0, output name:output_block1quanticonvolution0_conv_output
[16:15:19:134][INFO] [1655108119.528437276] [dnn]: The model input 0 width is 960 and height is 512
[16:15:19:134][INFO] [1655108119.528535271] [dnn]: The model input 1 width is 960 and height is 512
[16:15:19:134][INFO] [1655108119.528598393] [dnn]: Task init.
[16:15:19:135][INFO] [1655108119.530435806] [dnn]: Set task_num [2]
[16:15:19:135][INFO] [1655108119.530549051] [elevation_dection]: The model input width is 960 and height is 512
[16:15:19:158][INFO] [1655108119.559583836] [elevation_dection]: read image: ./config/images/charging_base.png to detect
[16:15:19:299][WARN] [1655108119.731084555] [elevation_dection]: start success!!!
[16:15:19:351][INFO] [1655108119.779924566] [elevation_net_parser]: fx_inv_: 0.000605
[16:15:19:383][INFO] [1655108119.780357879] [elevation_net_parser]: fy_inv_: 0.000604
[16:15:19:383][INFO] [1655108119.780576493] [elevation_net_parser]: cx_inv_: -0.604389
[16:15:19:383][INFO] [1655108119.780654031] [elevation_net_parser]: cy_inv_: -0.318132
[16:15:19:384][INFO] [1655108119.780751527] [elevation_net_parser]: nx_: 0.000000
[16:15:19:384][INFO] [1655108119.780858063] [elevation_net_parser]: ny_: 0.000000
[16:15:19:384][INFO] [1655108119.780962558] [elevation_net_parser]: nz_: 1.000000
[16:15:19:384][INFO] [1655108119.781067928] [elevation_net_parser]: camera_height: 1.000000
[16:15:19:385][INFO] [1655108119.781833267] [elevation_net_parser]: model out width: 480, height: 256
[16:15:19:416][INFO] [1655108119.808395254] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.808593786] [elevation_net_parser]: height: -42.699909
[16:15:19:416][INFO] [1655108119.808644533] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.808692531] [elevation_net_parser]: height: -25.339746
[16:15:19:416][INFO] [1655108119.808739279] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.808785527] [elevation_net_parser]: height: -22.111366
[16:15:19:416][INFO] [1655108119.808832774] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.808878606] [elevation_net_parser]: height: -25.339746
[16:15:19:416][INFO] [1655108119.808925645] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.808971809] [elevation_net_parser]: height: -21.989540
[16:15:19:416][INFO] [1655108119.809017516] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.809063138] [elevation_net_parser]: height: -48.303890
[16:15:19:416][INFO] [1655108119.809109678] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.809155592] [elevation_net_parser]: height: -32.527466
[16:15:19:416][INFO] [1655108119.809202548] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.809247880] [elevation_net_parser]: height: -32.710201
[16:15:19:416][INFO] [1655108119.809294669] [elevation_net_parser]: depth: 998.000000
[16:15:19:416][INFO] [1655108119.809340542] [elevation_net_parser]: height: -33.014767
[16:15:19:417][INFO] [1655108119.809387165] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809433454] [elevation_net_parser]: height: -35.451283
[16:15:19:417][INFO] [1655108119.809480202] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809527158] [elevation_net_parser]: height: -38.192360
[16:15:19:417][INFO] [1655108119.809573906] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809619820] [elevation_net_parser]: height: -34.233025
[16:15:19:417][INFO] [1655108119.809667235] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809713357] [elevation_net_parser]: height: -34.233025
[16:15:19:417][INFO] [1655108119.809759397] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809805686] [elevation_net_parser]: height: -33.014767
[16:15:19:417][INFO] [1655108119.809852643] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809899307] [elevation_net_parser]: height: -34.354851
[16:15:19:417][INFO] [1655108119.809945930] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.809991844] [elevation_net_parser]: height: -35.024891
[16:15:19:417][INFO] [1655108119.810038384] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.810084715] [elevation_net_parser]: height: -41.298916
[16:15:19:417][INFO] [1655108119.810131296] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.810268706] [elevation_net_parser]: height: -33.745720
[16:15:19:417][INFO] [1655108119.810317745] [elevation_net_parser]: depth: 998.000000
[16:15:19:417][INFO] [1655108119.810364285] [elevation_net_parser]: height: -32.710201
[16:15:19:417][INFO] [1655108119.810410741] [elevation_net_parser]: depth: 998.000000

log显示,读取本地图片推理之后输出image基于像素的深度和高度信息。