# 视频超分辨率

Source: [https://docs.qualcomm.com/doc/80-70017-50SC/topic/video-super-resolution.html](https://docs.qualcomm.com/doc/80-70017-50SC/topic/video-super-resolution.html)

**gst-ai-superresolution** 应用程序能够使用低分辨率输入生成高分辨率视频帧。

该图显示了 一个 pipeline，其接受来自文件源的视频流作为输入，使用 LiteRT 通过超分辨率模块对其进行处理，并显示输出。

有关 pipeline 中使用的插件的信息，请参阅 [Pipeline 流](https://docs.qualcomm.com/doc/80-70017-50SC/topic/video-super-resolution.html#video-super-resolution__section_kkk_xhz_lcc)。

Figure : gst-ai-superresolution pipeline（Wayland 显示）
            
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)

Figure : gst-ai-superresolution pipeline（文件接收）
            
            ![](data:image/jpeg;base64,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## 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
- 从主机推送文件：单个模型或者批量模型：

        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。
注释： 视频文件的预期分辨率为 128 × 128。

## 运行应用程序

- 使用 Wayland 显示器显示输出：

        gst-ai-superresolution --input-file=/opt/video.mp4 --displayCopy to clipboard
- 使用 filesink 将输出保存至文件中：

        gst-ai-superresolution --input-file=/opt/video.mp4 --output-file=/opt/out.mp4Copy to clipboard
- 使用 LiteRT 运行带有常量的模型：

        gst-ai-superresolution --input-file=/opt/video.mp4 --model=/opt/quicksrnetsmall_quantized.tflite --constants="srnet,q-offsets=<0.0>,q-scales=<1.0>;"Copy to clipboard

注释： `q-scales` 和 `q-offsets` 常量的值分别为 `<1.0>` 和 `<0.0>`。

要显示可用的帮助选项，请在 SSH shell 中运行以下命令：

    gst-ai-superresolution -hCopy to clipboard

如需停止用例，可按下 CTRL + C。

## 预期输出

输出显示在HDMI监视器上。

Figure : VSR 的预期输出
                
                ![](data:image/png;base64,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)

## Pipeline 流

下表列出了视频超分辨率 pipeline 中使用的插件：| 插件 | 说明 |
| --- | --- |
| filesrc | 采集视频流并使用 tee 拆分流进行推理。 |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvconverter.html) | AI 处理流将其用于预处理：<ol class="ol" id="video-super-resolution__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="video-super-resolution__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>张量数据流用于 pipeline 后期的推理。 |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimltflite.html) | 在 LiteRT 上运行并使用 quicksrnetsmall\_quantized模型。<ol class="ol" id="video-super-resolution__ol_lwl_521_mcc"><br>                                    <li class="li">推理 runtime 在其接收端上接收张量数据。</li><br><br>                                    <li class="li">Runtime 执行推理。</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> |
| [qtimlvsuperresolution](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvsuperresolution.html) | 处理任何超分辨率模式的推理结果。<ol class="ol" id="video-super-resolution__ul_w2c_xf1_mcc"><br>                                    <li class="li">加载 SRNet 模块。 </li><br><br>                                    <li class="li">生成视频帧形式的结果。 </li><br><br>                                    <li class="li">将它们发送至 qtivcomposer 的接收端。</li><br><br>                                </ol><br><br>关于 INT8 模型，添加以下常量：<br><ul class="ul" id="video-super-resolution__ul_eqr_zf1_mcc"><br>                                    <li class="li">q-offsets </li><br><br>                                    <li class="li">q-scales</li><br><br>                                </ul> |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtivcomposer.html) | <ol class="ol" id="video-super-resolution__ol_dmb_2vr_lbc"><br>                                    <li class="li">将接收端获取的内容组成帧。</li><br><br>                                    <li class="li">将包含这些组合帧的 GStreamer 缓存推送到其发送端。</li><br><br>                                </ol> |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70017-50SC/topic/waylandsink.html) | <ol class="ol" id="video-super-resolution__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> |

**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)

**相关概念**  

- [使用 LiteRT 进行视频超分辨率和显示](https://docs.qualcomm.com/doc/80-70017-50SC/topic/video-super-resolution-and-display-with-litert.html)

Last Published: Nov 11, 2025

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