# 目标检测和分类 

Source: [https://docs.qualcomm.com/doc/80-70017-50SC/topic/camera-ai-detection-overlay-composer-display.html](https://docs.qualcomm.com/doc/80-70017-50SC/topic/camera-ai-detection-overlay-composer-display.html)

**gst-camera-two-stream-detection-and-classification-side-by-side.py** 应用程序使用 YOLOv8 LiteRT 模型来检测和分类 AI Overlay Composer 显示的场景中的对象。

Figure : 目标检测和分类的 pipeline
            
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有关此 pipeline 中使用的插件的信息，请参阅 [Pipeline 流](https://docs.qualcomm.com/doc/80-70017-50SC/topic/camera-ai-detection-overlay-composer-display.html#camera-ai-detection-overlay-composer-display__section_l1h_cpk_bdc)。

## 模型文件

Table : 用于检测和分类的模型

| 目的 | LiteRT模型 | 说明 |
| :--- | :--- | :--- |
| 目标检测 | YOLOv8 | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ul_cfw_r4k_bdc"><br>                                    <li class="li">从摄像头流中识别场景中的对象。</li><br><br>                                    <li class="li">将边界框覆盖在检测到的对象上。</li><br><br>                                </ol> |
| 图像分类 | Resnet101 | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_jll_v4k_bdc"><br>                                    <li class="li">对摄像头流中的场景进行分类。</li><br><br>                                    <li class="li">在屏幕上叠加分类标签。</li><br><br>                                </ol> |

## 运行应用程序

1. 确保您已完成[前提条件](https://docs.qualcomm.com/doc/80-70017-50SC/topic/python-sample-applications.html#python-sample-applications__section_gm5_s5j_bdc)。
2. 在目标设备上运行检测和分类脚本：

        python3 /usr/bin/gst-camera-two-stream-detection-and-classification-side-by-side.pyCopy to clipboard

如需显示可用的帮助选项，可运行以下命令：

python3 gst-camera-two-stream-detection-and-classification-side-by-side.py --helpCopy to clipboard

Table : 用于目标检测和分类 python 应用程序的模型和标签文件的默认目录

| 模型和标签文件 | 目录 |
| :--- | :--- |
| 检测型号 | /opt/data/YoloV8N\_Detection\_Quantized.tflite |
| 检测标签 | /opt/data/yolov8n.labels |
| 分类模型 | /opt/data/Resnet101\_Quantized.tflite |
| 分类标签 | /opt/data/resnet101.labels |

## 预期输出

图像并排显示在显示屏上。

## Pipeline 流

| 处理过程 | 说明 |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtiqmmfsrc.html) | 从摄像头采集两个视频流：<ul class="ul"><br>                                    <li class="li">用于检测的流使用 tee 分割并发送到以下位置：<ul class="ul" id="camera-ai-detection-overlay-composer-display__ul_elf_dtk_bdc"><br>                                            <li class="li">qtimetamux 保留视频流。</li><br><br>                                            <li class="li">qtimlvconverter 将视频流转换为输入张量以进行检测推理。</li><br><br>                                        </ul><br></li><br><br>                                    <li class="li">用于分类的流使用 tee 进行分割并发送到以下位置：<ul class="ul" id="camera-ai-detection-overlay-composer-display__ul_nsj_htk_bdc"><br>                                            <li class="li">qtimetamux 保留视频流。</li><br><br>                                            <li class="li">qtimlvconverter 将视频流转换为输入张量，用于分类推理。</li><br><br>                                        </ul><br><br>                                    </li><br><br>                                </ul> |
| **预处理** | **预处理** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvconverter.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_i5w_4wl_vbc"><br>                                    <li class="li">在其接收端上接收视频流。</li><br><br>                                    <li class="li">执行预处理：<ul class="ul" id="camera-ai-detection-overlay-composer-display__ol_zdw_qwl_vbc"><br>                                            <li class="li">颜色转换</li><br><br>                                            <li class="li">缩小/放大</li><br><br>                                            <li class="li">当模型期望浮点值作为输入时对流数据进行标准化</li><br><br>                                        </ul><br></li><br><br>                                    <li class="li">在其发送端上将视频流转换为张量数据。<p class="p">分类模型使用此张量数据进行推理。</p><br></li><br><br>                                </ol> |
| **推理** | **推理** |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimltflite.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_u1l_cxl_vbc"><br>                                    <li class="li">加载模型。</li><br><br>                                    <li class="li">为选择的 delegate 修改图。</li><br><br>                                    <li class="li">在其接收端上接收张量数据。</li><br><br>                                    <li class="li">执行推理并在其发送端上生成包含推理结果的张量数据。</li><br><br>                                </ol> |
| **后处理** | **后处理** |
| [qtimlvdetection](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvdetection.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_ky5_grn_vbc"><br>                                    <li class="li"> 接收来自目标检测模型的推理张量。 </li><br><br>                                    <li class="li">将其接收端上的推理张量转换为多媒体插件稍后可以处理的视频或文本等格式。</li><br><br>                                    <li class="li">将阈值应用于所选的结果数。 </li><br><br>                                    <li class="li">加载检测模型的相应模块。 <p class="p">在此用例中，qtimlvdetection 执行以下操作：<br>                                            </p><ol class="ol" type="a" id="camera-ai-detection-overlay-composer-display__ol_jcd_wnk_5bc"><br>                                            <li class="li">加载 YOLOv8 子模块。 </li><br><br>                                            <li class="li">将结果生成为文本结构。</li><br><br>                                            <li class="li">接着发送到 qtimetamux 的接收端。</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtimlvclassification](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvclassification.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_o3v_2xl_vbc"><br>                                    <li class="li">从其接收端上的分类模型接收推理结果。 </li><br><br>                                    <li class="li">将推理张量转换为多媒体插件稍后可以处理的视频或文本等格式。 </li><br><br>                                    <li class="li">将阈值应用于所选的结果数。 </li><br><br>                                    <li class="li">加载分类模型的相应模块。 <p class="p">在此用例中，qtimlvclassification 执行以下操作： </p><ol class="ol" type="a" id="camera-ai-detection-overlay-composer-display__ol_p3v_2xl_vbc"><br>                                            <li class="li">加载模型的子模块。</li><br><br>                                            <li class="li">将结果生成为带有分类标签的视频帧。</li><br><br>                                            <li class="li">将它们发送至 qtivcomposer 的接收端。</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtimetamux](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimetamux.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_ll3_x5l_vbc"><br>                                    <li class="li">在接收端上接收视频流和文本流，以及与视频流相对应的边框结果。</li><br><br>                                    <li class="li">使用接收端中的视频流内容生成 GST 缓存。</li><br><br>                                    <li class="li">将边框作为 GstVideoRegionOfInterest 从数据接收端添加到其源接插口上的 GST 缓存元数据（元多路复用）。</li><br><br>                                </ol> |
| [qtioverlay](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtioverlay.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_wst_y5l_vbc"><br>                                    <li class="li">接收多路复用流。</li><br><br>                                    <li class="li">使用 CL 将边框叠加在 VideoFrame 上。</li><br><br>                                    <li class="li">在其发送端上生成带有叠加层的 GST 缓存。</li><br><br>                                </ol> |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtivcomposer.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_nmc_lxl_vbc"><br>                                    <li class="li">在接收端上接收原始视频流和分类结果。 </li><br><br>                                    <li class="li">在其发送端上生成 GST 缓存，其内容由来自其接收端的视频流组成。</li><br><br>                                </ol> |
| **输出** | **输出** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70017-50SC/topic/waylandsink.html) | <ol class="ol" id="camera-ai-detection-overlay-composer-display__ol_cgt_mwl_vbc"><br>                                    <li class="li">在其接收端上接收视频</li><br><br>                                    <li class="li">将视频流提交到 Weston。 </li><br><br>                                    <li class="li">Weston 在本地显示器设备上呈现视频流。</li><br><br>                                </ol> |

**上一级主题：** [Python 应用程序](https://docs.qualcomm.com/doc/80-70017-50SC/topic/python-sample-applications.html)

**相关概念**  

- [目标检测](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-object-detection.html)
- [分类](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-classification.html)

Last Published: Nov 11, 2025

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