Merge pull request #111 from zwyzwm/main

tdl add pedestrian detection

docs/duo/application-development/tdl-sdk/pedestrian-detection.md

@@ -0,0 +1,89 @@
+---
+sidebar_label: 'Pedestrian detection'
+sidebar_position: 20
+---
+
+# Pedestrian detection
+
+This test program will pull camera data, add pedestrian detection algorithm, and use VLC and other tools to pull the stream in real time to view the effect.
+
+### Compile
+
+Face detection program source code location:
+
+Duo256M and DuoS: [sample_vi_od.c](https://github.com/milkv-duo/cvitek-tdl-sdk-sg200x/blob/main/sample/cvi_tdl/sample_vi_od.c)
+
+Refer to the method in the previous section [Introduction](https://milkv.io/zh/docs/duo/application-development/tdl-sdk/tdl-sdk-introduction) to compile the sample program.
+
+### Upload the test program and model files to Duo
+
+- Refer to the method in the [Run Duo](https://milkv.io/zh/docs/duo/getting-started/boot) section to install the system
+
+- Refer to the method in the [Camera](https://milkv.io/zh/docs/duo/camera/gc2083) section to connect the camera and power on
+
+Upload the compiled `sample_vi_od` to the Duo development board through the `scp` command on the computer:
+
+```bash
+scp sample_vi_od [email protected]:/root/
+```
+
+Download cvimodel for pedestrian detection:
+
+https://github.com/sophgo/tdl_models/blob/main/cv181x/mobiledetv2-pedestrian-d0-ls-448.cvimodel
+
+Use scp to upload cvimodel to Duo development board.
+
+### Run the example
+
+Log in to Duo's terminal via the serial port or [ssh](https://milkv.io/zh/docs/duo/getting-started/setup#ssh) .
+
+Add executable permissions to the test program in Duo's terminal
+```
+chmod +x sample_vi_od
+```
+Execute the test program in Duo's terminal:
+
+Duo256M and DuoS:
+```
+./sample_vi_od mobiledetv2-pedestrian mobiledetv2-pedestrian-d0-ls-448.cvimodel
+```
+
+The Duo terminal will display information similar to the following:
+```
+[root@milkv-duo]~# ./sample_vi_od mobiledetv2-pedestrian mobiledetv2-pedestrian-
+d0-ls-448.cvimodel
+[SAMPLE_COMM_SNS_ParseIni]-1950: Parse /mnt/data/sensor_cfg.ini
+[parse_source_devnum]-1605: devNum = 1
+[parse_sensor_name]-1686: sensor = GCORE_GC2083_MIPI_2M_30FPS_10BIT
+[parse_sensor_busid]-1714: bus_id = 3
+
+...
+
+1 R:1464 B:2327 CT:3937
+2 R:1974 B:1613 CT:7225
+Golden 1464 1024 2327
+wdrLEOnly:1
+
+```
+At this time, point the camera at pedestrians, and the Duo terminal will print the number of pedestrians detected by the camera in real time:
+```
+obj count: 1, take 17.03,width:1920 ms
+obj count: 1, take 17.55,width:1920 ms
+obj count: 0, take 17.30,width:1920 ms
+```
+### Use VLC to pull the stream on the PC to view the effect
+
+Open `VLC media player`, click `Media` in the upper left corner, select `Open Network Stream`, and enter the URL.
+
+If you are using USB Net (USB-NCM), the address is:
+```
+rtsp://192.168.42.1/h264
+```
+
+<Image src='/docs/duo/duo-vlc-stream-setup.jpg' minWidth='40%' maxWidth='60%' align='left' />
+
+If you are using the network port on the baseboard IO-Board, or the network port integrated on DuoS, the IP address in the URL needs to be replaced with the IP of the network port (you can use the `ifconfig` command in the Duo terminal to view it).
+
+Click the `Show more options` option in the lower left corner, and you can set the `Caching` option to adjust the delay. The default is 1000 milliseconds, which is 1 second. When the network environment is good, such as in a local area network, you can lower it to reduce the delay. It can be set to 100 to 300. If the network environment is poor or the screen is stuck, you can try to increase it.
+
+After configuration, click `Play` to view the pedestrian detection effect of the camera.

i18n/zh/docusaurus-plugin-content-docs/current/duo/application-development/tdl-sdk/Pedestrian-detection.md

@@ -0,0 +1,92 @@
+---
+sidebar_label: '行人检测'
+sidebar_position: 20
+---
+
+# 行人检测
+
+该测试程序会拉取摄像头数据，加入行人检测算法，使用 VLC 等工具可以实时拉流查看效果。
+
+### 编译
+
+人脸检测程序源码位置：
+
+ Duo256M and DuoS：[sample_vi_od.c](https://github.com/milkv-duo/cvitek-tdl-sdk-sg200x/blob/main/sample/cvi_tdl/sample_vi_od.c)
+
+参考上一章节 [简介](https://milkv.io/zh/docs/duo/application-development/tdl-sdk/tdl-sdk-introduction) 中的方法编译示例程序。
+
+### 上传测试程序和模型文件到 Duo 中
+
+- 参考 [运行 Duo](https://milkv.io/zh/docs/duo/getting-started/boot) 章节中的方法安装好系统
+
+- 参考 [摄像头](https://milkv.io/zh/docs/duo/camera/gc2083) 章节中的方法连接摄像头之后，上电开机
+
+将编译生成的 `sample_vi_od` 在电脑上通过 `scp` 命令上传到 Duo 开发板中：
+
+```bash
+scp sample_vi_od [email protected]:/root/
+```
+
+下载用于行人检测的 cvimodel :
+
+https://github.com/sophgo/tdl_models/blob/main/cv181x/mobiledetv2-pedestrian-d0-ls-448.cvimodel
+
+同样用 scp 将 cvimodel 上传到 Duo 开发板中。
+
+### 运行示例
+
+通过串口或者 [ssh](https://milkv.io/zh/docs/duo/getting-started/setup#ssh) 登陆到 Duo 的终端。
+
+在 Duo 的终端中为测试程序添加可执行权限
+```
+chmod +x sample_vi_od
+```
+
+在 Duo 的终端中执行测试程序：
+
+Duo256M 和 DuoS：
+```
+./sample_vi_od mobiledetv2-pedestrian mobiledetv2-pedestrian-d0-ls-448.cvimodel
+```
+
+Duo 终端中会显示类似如下信息:
+```
+[root@milkv-duo]~# ./sample_vi_od mobiledetv2-pedestrian mobiledetv2-pedestrian-
+d0-ls-448.cvimodel
+[SAMPLE_COMM_SNS_ParseIni]-1950: Parse /mnt/data/sensor_cfg.ini
+[parse_source_devnum]-1605: devNum =  1
+[parse_sensor_name]-1686: sensor =  GCORE_GC2083_MIPI_2M_30FPS_10BIT
+[parse_sensor_busid]-1714: bus_id =  3
+
+...
+
+1 R:1464 B:2327 CT:3937
+2 R:1974 B:1613 CT:7225
+Golden 1464 1024 2327
+wdrLEOnly:1
+
+```
+此时，将摄像头对着行人，Duo 终端中会打印摄像头实时检测到的行人个数：
+```
+obj count: 1, take 17.03,width:1920 ms
+obj count: 1, take 17.55,width:1920 ms
+obj count: 0, take 17.30,width:1920 ms
+```
+### PC 端使用 VLC 拉流查看效果
+
+打开 `VLC media player`，点击左上角 `Media`，选择 `Open Network Stream`，输入 URL。
+
+如果使用的是 USB Net(USB-NCM)，地址为：
+```
+rtsp://192.168.42.1/h264
+```
+
+<Image src='/docs/duo/duo-vlc-stream-setup.jpg' minWidth='40%' maxWidth='60%' align='left' />
+
+
+如果使用的是底板 IO-Board 上的网口，或者 DuoS 上集成的网口，URL 中的 IP 地址需换成网口的 IP（可在 Duo 终端中使用 `ifconfig` 命令查看）。
+
+点开左下角的 `Show more options` 选项，可以设置 `Caching` 选项来调整延时，默认是1000毫秒，也就是1秒。网络环境较好时比如在局域网内，可以将其调低来降低延迟，可以设置为100到300。如果网络环境较差或者画面出现卡顿时，可以尝试将其调高。
+
+配置好之后，点击 `Play`，即可查看摄像头的行人检测效果。
+

sidebars.js

@@ -57,6 +57,7 @@ const sidebars = {
             'duo/application-development/tdl-sdk/tdl-sdk-yolov5',
             'duo/application-development/tdl-sdk/tdl-sdk-yolov8',
             'duo/application-development/tdl-sdk/tdl-sdk-yolo11',
+            'duo/application-development/tdl-sdk/Pedestrian-detection',
           ],
         },
         {