# 人脸识别

Source: [https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-face-recognition.html](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-face-recognition.html)

**gst-ai-face-recognition** 应用程序从摄像头或 RTSP 流收集实时视频输入，并共享此输入以进行人脸检测和识别。它使用 three\_dmm Qualcomm AI Engine Direct 模型进行人脸检测。结果是在 HDMI 显示器上预览叠加的 AI 模型。

注释： 此示例应用程序目前不适用，它将在未来版本中得到支持。

该图显示了一个 pipeline，该 pipeline 接收输入，执行预处理，在 AI 硬件上运行推理，并在屏幕上显示结果。

Figure : gst-ai-face-recognition pipeline
            
            ![](data:image/png;base64,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)

有关 pipeline 流中使用的插件的信息，请参阅 [Pipeline 流](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-face-recognition.html#gst-ai-face-recognition__section_mrl_x4m_qdc)。

## 前提条件

- [下载 LiteRT 和 Qualcomm AI Engine Direct 的模型、标签和 config JSON 文件](https://docs.qualcomm.com/doc/80-70017-50SC/topic/ai-ml-sample-applications.html#ai-ml-sample-applications__section_fsl_lgz_scc).
- 要访问您的主机设备，请启用 SSH。相关说明，可参见[使用 SSH 登录](https://docs.qualcomm.com/bundle/publicresource/topics/80-70017-254/how_to.html#use-ssh)。
注释： 如果 SSH 已启用，则可以跳过此步骤。
- 进入 SSH shell 并运行用例：

        ssh root@<ip-addr of the target device>Copy to clipboard
- 启用显示屏：

        export XDG_RUNTIME_DIR=/dev/socket/weston && export WAYLAND_DISPLAY=wayland-1Copy to clipboard
- 从 Linux 主机推送文件：

        scp <filename> root@<IP address of target device>:/opt/Copy to clipboard
- 将 video.mp4 文件推送到 opt 文件夹中。

## 运行应用程序

注释： 以下命令提供默认模型和标签路径。如果您的文件夹结构不同，请替换命令行参数中的默认路径。参见[示例模型和标签文件](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-face-recognition.html#gst-ai-face-recognition__section_bxr_x4m_qdc)。

请使用以下语法，运行该应用程序：

    gst-ai-face-recognition [OPTION?]Copy to clipboard

以下是各种用例：

- 使用 DSP runtime 以及来自主摄像头的输入运行推理：

        gst-ai-face-recognition -c 0Copy to clipboard

    关于辅助摄像头，将 `-c` 替换为 <var class="keyword varname">1</var>。
- 添加模型和标签路径作为参数，并使用 Qualcomm Neural Network 和主摄像头的输入运行推理：

        gst-ai-face-recognition --face-detection-model /opt/face_detection.so --three-dmm-model /opt/three_dmm.so --face-recognition-model /opt/face_recognition.so --face-detection-labels /opt/face_detection.labels --three-dmm-labels /opt/three_dmm.labels --face-recognition-labels /opt/face_recognition.labelsCopy to clipboard
- 使用 DSP runtime 以及来自 RTSP 流的输入运行推理：

        gst-ai-face-recognition --rtsp-ip-port="rtsp://<ip-address-of-device>/30fps.mkv"Copy to clipboard

请在 SSH shell 中运行以下命令，以显示可用的帮助选项：

    gst-ai-face-recognition -hCopy to clipboard

如需停止用例，可按下 CTRL + C。

## Pipeline 流

下表列出了人脸识别 pipeline 中使用的插件：| 插件 | 说明 |
| --- | --- |
| 摄像头源：[qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtiqmmfsrc.html) | <ul class="ul" id="gst-ai-face-recognition__ul_zyl_gj1_mcc"><br>                                    <li class="li">从摄像头采集实时流。</li><br><br>                                    <li class="li">使用 tee 拆分流进行推理。</li><br><br>                                </ul> |
| 文件源：filesrc | <ul class="ul" id="gst-ai-face-recognition__ul_z1z_x4f_w1c"><br>                                    <li class="li">使用 filesrc 采集视频流，然后使用 qtdemux 对视频流进行解复用。</li><br><br>                                    <li class="li">使用 tee 拆分流进行推理。</li><br><br>                                </ul> |
| RTSP 源：rtspsrc | <ul class="ul" id="gst-ai-face-recognition__ul_vsj_2r4_tbc"><br>                                    <li class="li">使用 rtspsrc 采集 RTSP 流，然后使用 rtph264depay 进行视频提取。</li><br><br>                                    <li class="li">使用 tee 拆分流进行推理。</li><br><br>                                </ul> |
| h264parse | 渲染 H.264 视频。 |
| [v4l2h264dec](https://docs.qualcomm.com/doc/80-70017-50SC/topic/v4l2h264dec.html) | 解码视频 |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvconverter.html) | <ol class="ol" id="gst-ai-face-recognition__ol_j34_ddg_q1c"><br>                                    <li class="li">在其接收端上接收视频流。</li><br><br>                                    <li class="li">对流数据执行以下预处理。当模型需要浮点值作为输入时，会执行此预处理。<ol class="ol" type="a" id="gst-ai-face-recognition__ol_m5z_cpr_lbc"><br>                                            <li class="li">颜色转换</li><br><br>                                            <li class="li">缩放（向上或向下）</li><br><br>                                            <li class="li">归一化</li><br><br>                                        </ol><br></li><br><br>                                    <li class="li">将预处理的视频流转换为其发送端上的张量数据流。 </li><br><br>                                </ol><br><br>                                <br>张量数据流用于 pipeline 后期的推理。 |
| [qtimlqnn](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlqnn.html) | 充当 Qualcomm Neural Network 模型的推理插件。<ol class="ol" id="gst-ai-face-recognition__ol_mbk_pl3_4dc"><br>                                    <li class="li">推理 runtime 在其接收端上接收到张量数据后，会运行推理。</li><br><br>                                    <li class="li">生成一个张量数据流，并在其发送端上显示推理结果。</li><br><br>                                </ol> |
| [qtimlvdetection](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvdetection.html) | <ul class="ul" id="gst-ai-face-recognition__ul_lwr_xl3_4dc"><br>                                    <li class="li">处理来自任何人脸检测模型的推理结果。</li><br><br>                                    <li class="li">将阈值应用于所选结果数。</li><br><br>                                </ul> |
| [qtimetamux](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimetamux.html) | <ul class="ul" id="gst-ai-face-recognition__ul_cvw_j3n_qdc"><br>                                    <li class="li">从 qtimlvdetection 接收人脸检测模型的输出并将其进行多路复用。</li><br><br>                                    <li class="li">从 qtimlvpose 接收面部姿态的输出并将其进行多路复用。</li><br><br>                                </ul> |
| tee | 分割流以进行推理。 |
| [qtimlvpose](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvpose.html) | 执行面部姿态识别。 |
| [qtimlvclassification](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvclassification.html) | 接收来自 qtimetamux 的流并对人脸进行分类。 |
| [qtioverlay](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtioverlay.html) | <ol class="ol" id="gst-ai-face-recognition__ol_wst_y5l_vbc"><br>                                    <li class="li">接收多路复用流。</li><br><br>                                    <li class="li">将边界框叠加在流上。</li><br><br>                                </ol> |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70017-50SC/topic/waylandsink.html) | <ol class="ol" id="gst-ai-face-recognition__ol_kjr_fvr_lbc"><br>                                    <li class="li">Waylandsink 将其接收端上接收的视频流提交给 Weston。</li><br><br>                                    <li class="li">Weston 在本地显示器上渲染视频流。</li><br><br>                                </ol> |

## 示例模型和标签文件

Table : gst-ai-face-detection 的示例模型和标签文件

| Runtime | 模型文件 | 标签文件 |
| :--- | :--- | :--- |
| Qualcomm AI Engine Direct | <ul class="ul" id="gst-ai-face-recognition__ul_bdk_hwm_qdc"><br>                                    <li class="li"><var class="keyword varname">face_detection.so</var></li><br><br>                                    <li class="li"><var class="keyword varname">face_recognition.so</var></li><br><br>                                    <li class="li"><var class="keyword varname">three_dmm.so</var></li><br><br>                                </ul> | <ul class="ul" id="gst-ai-face-recognition__ul_q4l_kwm_qdc"><br>                                    <li class="li"><var class="keyword varname">face_detection.labels</var></li><br><br>                                    <li class="li"><var class="keyword varname">face_recognition.labels</var></li><br><br>                                    <li class="li"><var class="keyword varname">three_dmm.labels</var></li><br><br>                                </ul> |

**上一级主题：** [AI/ML 示例应用程序](https://docs.qualcomm.com/doc/80-70017-50SC/topic/ai-ml-sample-applications.html)

Last Published: Nov 11, 2025

[Previous Topic
人脸检测](https://docs.qualcomm.com/bundle/publicresource/80-70017-50SC/topics/gst-ai-face-detection.md) [Next Topic
使用 Python 和容器进行图像分割](https://docs.qualcomm.com/bundle/publicresource/80-70017-50SC/topics/image-segmentation-using-python.md)