# 多输入 AI 推理

Source: [https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-multi-input-output-object-detection.html](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-multi-input-output-object-detection.html)

**gst-ai-multi-input-output-object-detection** 应用程序使您能够对来自不同来源（如摄像头、文件）或通过网络（如实时流协议（RTSP））的多个视频流执行目标检测。

下图显示了 pipeline 工作流，该工作流从不同源（如摄像头、文件或 RTSP）采集视频流进行推理。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/gst-ai-multi-input-output-object-detection.html#gst-ai-multi-input-output-object-detection__section_qbz_bsq_nbc)。

Figure : 多输入 AI 推理 pipeline
            
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## 前提条件

1. 下载 [YOLOv5](https://github.com/ultralytics/yolov5) 模型。
    运行 yolov5.tflite 模型需要 Python 环境。

注释： 根据主机环境中的 Python 版本修改以下命令。
2. 创建 Python 3.8 虚拟环境：

        sudo apt-get install python3.8Copy to clipboard

        python3.8 -m venv py3.8Copy to clipboard

        source py3.8/bin/activateCopy to clipboard
3. 生成 yolov5.tflite 模型：

        git clone https://github.com/ultralytics/yolov5.gitCopy to clipboard

        cd yolov5Copy to clipboard

        python -m pip install -r requirements.txt tensorflow-cpuCopy to clipboard

        python export.py --weights yolov5m.pt --img 320 --include tflite --int8 --data data/coco128.yamlCopy to clipboard
4. 在主机上，将模型推送到设备：

        scp yolov5m-int8.tflite root@<IP address of the device>:/opt/yolov5.tfliteCopy to clipboard
5. [下载 Qualcomm Neural Processing SDK 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_chl_dgz_scc).
6. 启用 SSH 以访问您的主机设备。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。
7. 进入 SSH shell 并运行用例：

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

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

        scp <filename> root@<IP address of target device>:/opt/Copy to clipboard

## 运行应用程序

注释： 对于 QCS8275，不支持摄像头用例。请使用文件或 RTSP 作为输入源。

YOLO-NAS 和 YOLOv5 模型在相同的 Common Objects in Context（COCO）数据集上进行训练。

进入 SSH shell 并将 YOLO-NAS 标签文件复制至 YOLOv5：

cp /opt/yolonas.labels /opt/yolov5.labelsCopy to clipboard

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-parallel-inference.html#gst-ai-parallel-inference__section_pnn_hmb_4dc)。

- 对来自两个摄像头的流运行 AI 目标检测：

        gst-ai-multi-input-output-object-detection --num-camera=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard
- 对来自文件源的数据流运行 AI
                        目标检测并显示输出：

        gst-ai-multi-input-output-object-detection --num-file=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard

    视频文件的默认源路径是
                            /opt/video1.mp4 和
                            /opt/video2.mp4。
- 对来自 RTSP 源的数据流运行 AI 目标检测并显示输出：

        gst-ai-multi-input-output-object-detection --num-rtsp=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard

    RTSP 源的默认 ip：端口号为 <var class="keyword varname">127.0.0.1:8554</var>。
- 从文件中获取输入源视频流，并显示输出，如下所示：
    - 在屏幕上显示输出。
    - 将输出保存在文件上。
    - 使用 RTSP 流通过网络发送输出。

    在执行此用例之前，请确保评估套件 (EVK) 和主机连接至同一网络：

    在 shell 中运行用例：

        gst-ai-multi-input-output-object-detection --num-file=2 -d -f /opt/app.mp4 --out-rtsp --model=/opt/yolov5.tflite --labels=/opt/yolov5.labels -i <evk-ip-address> -p <port_num>Copy to clipboard

    如需在主机 PC 上查看 RTSP 流，请执行以下操作：

    - 在主机上安装 VLC Media Player 并设置环境变量。
    - 在 Linux 主机上，执行下列操作之一以查看 RTSP 流：

            vlc -vvv rtsp://<evk-ip-address>:<port_num>/liveCopy to clipboard

            ffplay -rtsp_transport tcp rtsp://<evk-ip-address>:<port_num>/liveCopy to clipboard
    - 在 Windows 主机上，执行以下操作：
        1. 打开 VLC 媒体播放器。
        2. 选择 Media<abbr> &gt; </abbr>Open Network Stream 或按 CTRL +
                                        N）。
        3. 输入 `rtsp://<evk-ip-address>:<port_num>/live`。
        4. 点击 Play。

注释： 确保来自摄像头、RTSP 和文件源的输入流总数不超过 6 个。

要显示可用的帮助选项，请在 SSH shell 中运行以下命令：

    gst-ai-multi-input-output-object-detection --helpCopy to clipboard

如需停止用例，可按下 CTRL + C。

## 预期输出

处理后的结果显示在 HDMI 屏幕上，保存为 H.264 编码的 MP4 文件，或通过 RTSP 服务器进行流传输。

Figure : gst-ai-multi-input-output-object-detection 程序的预期输出
                
                ![](data:image/png;base64,UklGRshtAABXRUJQVlA4ILxtAABwmQKdASrPA24BPwFwsFArJqUjKjJd8WAgCWNBSuSVhkyDKz83veB06lVx+4B/hPC9dv1/Ux/cvTP6T/9m6GP/g+sfot/Wd/svqG/wD/fetn6zf+v9cLStvUnmW868bny/3utIrM/al+IX+/GT9ctSnGn/3+INfrwneRhGh/7vPe5hmXn1Xv/bv7ThHkkvmr6qVP2fkz1siuBejlL/fY8nWUDwn7tur6AkvaoJxMF65Fbo3zWT4ZDr0eB5yO/aQplq7yEhjGh9Cw8J+7ZMR+9tF3NFM2XOavMqCFYq3mDSwMhVZMyoqPoPMOvHafVqEySFguPDWA7jL4bba0nR4m2vKky0tVh3THp3YqYXUNTEFEC+BMCJXK6BtkRkIl35EWoL+x15z388JnKp7E64y4bgRYWHre6tPkxb9JOhW/Z3NbiMxh7dZ5JfZQDP407pySGJcji0bzDroNrZXsT7EZxtF/BR80oaej8NCqj8lSQW4rq82qbUCBXxL+rN5/dIRfrioKOn4AMVm8zIIcK6LTcOStJBrahtkAfAC64Xk0yUEK0lhj+xlLqEtqqAk/FLI9lsHws6se+kLDoOrYB8kGZSwljL7PzrWN4ILgCAqY/Rw15MTSijErtB9NDl7X9gkZQ76RkliC93cyDCMp3z0cIYmCZ4dJp6Uwhm9g5KF+I+hoy+CVPv1ZkupB4M/i1SFKhRKxGO3R60ubWil7wt1pQzX33GQ2u1BWpiVKtDz+y8TUp8hYuHIrRdpI9UfnupWa+iZKqnlo1p2fkj4N0kL0a2srgOiRM3yoda+jJxshoyV/diJOu5oaoD3trTIJT4coOphHnNbPBiJTX1Nb0uwv/PZEffbuPsiXBks0/miUnp4I+iWNlbgvitO0ub2qjCmLnNufBeKFdZFzZtlU7wzFENT61KZjfCggvm0THrx6rOTvxsVTLF1yaUJd+SIWVdnqPayq8BHVhxRc5/ur8rhbIANpdHIsy0pM265JpxJiybSg1dNWBlD9IZ/ijQHIrIl0mI5Ds3bshO4+Lfb+ir/5Ca6muzlBvvD49fCQu8bLMs0b4t+v/EfoUoJpD8RR9aoXTVALdJLH3oO4D76gL3y3VhA8N/TT2Ck97fE8eYzyz4jJ5ru0J3MpXpW0sDGgU4HuRXZEAvmxj3AdhyBoAaM4QBzWHKv774+V4JEuV1g+cGEZy4tokvByrgK74qipZLzJLM2jljAQSV9fUk+ywbJZsQzrC27alL5CRccK+3wndudlfLJ1kBmbbBGxq6Kr+xYZA3SxiwzMFeVvRTFkpa2julqu9UwwmbsodNEmv5+H/d7krqpuVaDJbuqpUABK5UGw7eAfy/NB2sVpdUYWL3kgallaVRUnr6OgWY7SseaYMkNUZeOu/7UZ3IpqiKhjDEcXNiNMwLI4HQA62eEpl7EU6fizysBFPHLL6cfyAMtbSFzEMN/Xdmt6BEpl4n5EjRLYF/KkIAkciFmtICWLjYc02QNhAjtm4q7dt/5QJcHH+KfP/KnCZMnWX/wqiGOBfIAe7ZmU3frE3OROl6bp2JnQFtQtzUiyyZsi5X3zQqhfjeQDf0+2h31det/qxgMKO9tITwIJBALl3oReSE0Ns+w0vYPpvpxrk8eqa23xV7aGPra4VCUymqf+tP38fQtsx3LhPT0T9bF5pzCD8C2YJ+Lh5oJZrbpwwUO4+eyLLnD6M6sEeuLV6nJhgYW4BXb5Ml6HemjIofLnzDCbczeBKTrYS0ZmFqWAb6R4/txuSzoh5iTRO3XAzhxIAtleKi7OcKauCYblfv4XO5IBBXmSctQXwH5xJofoUKQFWPtZJc+9wO4NMA205YFdyTjr5hkZPKX+Rx1nRf7mitT9Ls7Z2wKbC9L9TY4tpi7B2ar/UGul92Fs8rgVvyuoPNIsfzTIu3/I0xzo/gkIr+ZPc1bqDlQsxVPEHCkEzX6OT8900/OE5JqW/iANlps9o3U/v4rN3im3dgqvXi9Zk5kqaE2F4AGSj4H99otIZ8Z5LdSs9H/pVmBQD/8cuXNLpS4rN5jtjGNo316BI4F4HRkdDsNuq/RJITVIv+uRFRKaB1uu1FCcjNMCIZ2NMLumHuX//GAJCzm1RXYs3qjjGW68xGAUf5hptj9oa9dIIwmlBhfEqzBZQ4d3Ofx63jaA60qIzjspPspxbCdkTHkLg0KGZ1Ps0+PSaZzxnVD7IvtGW4mkqcRwrIoHimIbMef7zkveqcSLaQl9KjbdlZiKQJ52cIYh4/f9gOfoNw5q4bW9za/1lyxTg3HZrrb7tPH593x3gThGzd24PS2GQqc/4eFbBZN5+1eSVGtuuyNBqorTNbpIz7O2FPOcvOT8UI0kQzB5mlBXQ8zYJr4kiHSLoWOBWAR6RJi7QXZ5Z/4z3f0wVJl2sOi44aqzM67Vr9I1WPDYMVmXDt6v8dcmKPcNW2M0ZvCfxqMMcrMl+wg8sLW7az7Uef2r/WzQ5tszgJ/KBx9mLMxV5PnVirYxfvh0y/HTn/YUKbbluFEA711RPs6B6+eZpiWgBZg0TGFbC5EM9ghcoAZYiMTdY2RY/98EObQ61VXtQpaXcvw2JJG0TmWNgHb53XAXkj7L8rBomkzVcfgTGe2CmVedr8xll3W/tsIzVNE/EMMjYr3trp4zLKAus5ZIBnRo1Kfd6axyRZfHS9e7E7ioh/Eeru/nsKxIIcRguaT7Din5/KYgad25bmxZjxfuswO7f0NXMfOvLcWyJ8G40HAyNg8nrYS/s5c8Rg8GplT2U+S6m1ZQTxk6KgQgggJfXBq05L5QQpFPQ8OYGN+DQrasll11iGtFXspIllt0LiBpCgf0DDmvYPM182LkHjyHwiNPEqbv70FBjNVct/y2/CIKqhTxC7piCV6gahoJsrD+vJBIIIgigJuamftdnWTaPCRQV0OMhVkcpMAm6t9cux3QpW62IdepFhEOTjEi+dA5iFjK49IJAIarW0QLZlYhjOfzU6BdGlkBY7FscAD9ecYcoVYbo2OFNcmendjkz0HmIyx9soRjY3GZBmUZO6w1mDhZKpjq2e7EHjoTVUP+boW4lWEqCWpTtMuxgDhij22nqkMFlGi1W7tK7uUh1eslLJCjS+LPsVrQP4LoVxr4tmkZ1ZvJiPn1s9nqwhe7JyS5vCDdiAMjV2VL61Ld6edZuiE3LfcYVZWK2FcFRRtJXb0YVt2g1DJ6aftC5Y7O4I+XZKPTGA1lEXnVS/1yk8GNOkGheQUhMf69YpZjTKgU7TdyT3pXsk/LGwdObPmRSGontUDp3LuyKgv7QQQNpqoBW/aqws7h2BbxjThA51rvTx1bE2BggdHgGjZ17VyCa+Tr26EgLV+4+g8xH1Q0quB4GZGAokFXA02+UA2yGQhbcvRLUGrM9LwHLzw1PS7BwKUAkJUu24LV6P8P33XX06OsMz6UaM4k710fpKPNu9Jqqi9wkPn0BncI2tEyFR8wZToBQZUmWWyYFNJzUOnRAtaUBKOPNIw7f+7nnXQrkdyt0s2YBbdehyn3+F23UTFZi5Qe2ZGdRioNSp/k/7svEfUS8hb8sArefcTHAtFdqyLZhUnODNESg/YzCZDrCV4lkz5gM9cIQobbZmh5WND+afbP60YyPxIANukUVItspYBG/BLPUrBcAk9I8Z+0DR+1gbxZ0L9/u4gjO2+s9Ax1V57SLNsoz6cNPuSIkQWOmwa3yh3ukWEJJQAINTY4aSyS3FIUdnZi86eC82CSVZzVHRssYr5JtoMfabnVT129cP5ZLxuKzPiL5XU3mvZpx+B10BzCZzv/ODuMReDI3qeMbr/ZmUyhlWcAKiJ54BWZd4vB0Nv8MV+0SWxLjfQjqYGvUNGc8pN9MT/Hp6MOkfTL1mnuzkHFkvZpBaK11/YbAgunanvOqvgiP84ma0dvkshoMvVcOEbIsFdKMf/SF1zaE1kTBdW9HNNe7ln4BbSDa3D8U3YAN/Kg2p5tHW7CkCNuNtB7YHbDPNMnsBjjaHPxz/q/qq2Q9c7KSaoAby19Yq5CW6cDzr1qJZk2jQf7H5YqkusJ+AC8WgsH3Gbwa7/q7pzcLEuuTAJ4zwePbszqS20n4BIQxezDZC0IeMkewU9lo0CNCtEK0RBnOYvqbWY8oqjvYw2v3nPPwgmIm/woQQlk0Tvwv/e1iRWChgO73PmJNa/eFxkkx4c6ArqQt8sCYn9L5d7JqHTFq28WosdC80+7iJaOJFG0e7dimbRg7zqENxa7BoSOrwEwztJdgjt2YNSRmMo/fsH1a88+quOGEWHWY+GhRPzbKmTx7CrdrRE5APJl3Pr7uPvKfOF64IlmqutYmCcxmiVFPDLMsWfoe3cNbB8JvVd3nSoJz1JITrUreQshkb9Lb04ogi1CQjyHhMZXK6FGQDn4S/6BFpBNwongMtDsatwclycj4mVR31ITmNlmBxzFImtFz+fj+BCrALAScbdNbztZFh+ngVIXo5exn+b0KlsYE0sOlOf+2HQTz5AwtTDfuZw7yvRCvAP2Feg5KW9VGuDWWZV5SdSThkkhKCJF3tts8gELuFor5Lzeqn4u3rFhO1soYMXaUGm00B1kRO31cS3lh3jZEcuMfEbuyRgkTPDdgDbTgFzhoK4hCEsZVGdq0rbe6a05Ilw+JR6ToGEAEsfs+lWgFQyB7kEEy6Q8RICgTk/bMZ419pNVq/UQauK6twTiWFr+oKPkOwykQDi/6ZqIYs+5yYeTqj6YtwOl6sDLQACdWgfaetNJjoH+A+/ccMKDtN/1qUKFOgRz8t7rybNkYGIZJlSEb9RKhwoNfpXLXBSc3TCnvheok1OmMMirC9NwPVXn7P9tqJdhAQhSjZ3GSijfWNypXwl5HKP+eKBv3jhK4ligqGDBvHpA0dugvECsAmRn7K8kvpAm90yrO3GIqURGYOxB0V5CN6mV4neMz8Ph05eWZIEngYubec79iaMh9SnYUInujRnU9JwXfw0tDo6q97VurxwAeyidrKga81ppUllJeroT7SvDOu5p77mwvrfqA+hrWCDwqb8V7kxlI/Pze3Xk7wayfMDIRay120QsErF0VPhOw6O4MazppF5W3qK7gMUucXKeBEPplVte5bYWkA6ARyUrrck2jQNm5VxtgtsLrNosVkbRSpZL4drvyUtFgPaayasP4tXTMpIVQedC+ZFBZGJySPaZxvh7HaTAx2EXoO7rSntabsqFfambP/BhVrNtEEsVlTEw3tb0/TCEekogVpW4Y5qK8hfKHMcVIG+BTQcGEKrpA2e0WIg5chL0ttAp5dS1TDfEXMk9SocScNnfMJtM2l/6ijdXT9VS43QPpt7sh24oMmES/GsNMPl95xpnLd5wKp8PsXgQ130pZG6TZ81NLMvqsdstLK1aJaNktctzzikTB6P8SZDjnE3ZlezrwkodPSYUFDXdBZ1BhfUGjjXOs+jeH0tNn/X8vIsqABIHCA9YIwf4FGZAj90gAwmEq4rFwrPVxHzRPpXT2v3SPIMbntVikNNsDvqfJMm2+jMh5A1ePYojs2BUU8evsk8FWJIpfb2auXdgzvFGUEBtOFrfgFENTgQDbzYxnyP2CA1iKJFUbXqEappBrzLe+PYYT6FfwsiIlKa5ADm0U6ZyRsOz1xYHBt6acMXf7Nq+0kp01GavlDl5kBlRt51mG/lmKMIwEBEuW8O7aQwmnqbS2anHd/aovK3RO8zzHQV0JzxCmtrPP3NgoJS/unI+JAUeph1Wl2mPga+LtzKDfPYycHCdFET5Gu4X2nm23YSqwc2G5cBeprJK4baCeYJSC98uAqdb6BHzwqZJFsCFRVKfBllCZOAC654POn1zGgZKaKH5XnLrVnX122xQ7X5isCCNkbtdOUsSgLVFzH6BWQp8WiUNFEhrJAwq+JAC40ZHT6cV7UkzmOAHJrsKPSJFM+Pb8gGT3RVBY9FAZjpRdb2FAgi2Yi3TR9NoPfbSACs+tzE7Pkwb33OZN0+IYtbVd2i1EHkF8ZQdlmtXERX/AVX9pSRiRM+hLuaaci5fwbOlRIi4gCMNuPKtEKkDxJlHgWmaXQK5/zgAi+DfwHBxK8TuiZdRhiPQisJclGRzdTsNTDI3XRDrXQOTOSvk8F1h5SEJrXMO1GoxbkvEVGOYnulxXdZG0nnH4dAvLFnNaF9AEbbvhiv6X+WXLLuw897ogQ/nFUBe7i1TEQi3Xq5WXCr+X9kkP0gLUTjz586uNRCWwxhuVf5s0kMEmrkZHJ5vNqjS6pNpKSCPCaAWDUwgR+pFU/TBUg//a7tlv6GB81fFd4dneYIuhawmqqmcBAD22GiIguhfz6f/DHH/4Al4YdhP5FEWoY1ADemBr26XXKIFfK1ySuDFRHXf+VA+mGBMgJS3pXg84T6qGUojVvRqdGa5KuEhfA+APFwrQK/G4CIGtE4+wo9wC0R8tOTdJ7FUDgutxdZX7NX1rVZvQ8eyFE/aelkexDeUqVEL5d/IuyqrvMS8/UG5UXPl1mmxlTvdijMZt76B4axHvJkvkGAU1vzN6W12YtaP/XHoW9tK8AcThzVtSZ5SQuqJ7Amo53tU9lZxlryhPYLXAHypzRxGSJP84vEd3RN0YBpiiNhC40bwVXNfExC48NByf2Z4jg/OCOXJAUshcU+Q3/dj+blnTf1AJISpmi76q/KvP8bZ6qj0ZpK3/nSXMvYpAugs9jCHpS0EVglAZtswgtD6xSjgqlQL+1NWkUHJnxTPlaEBkesKtFwmQ8kx+AMHMJfs0tC7n9xuekf4ARvR68MRYoWav92ATcPrKqAGmi/k1P9tOnpzQr88eui8tPb6vaUgIDWa35FGIIOD1ngv+QZjMqrshR4rnzcFSzHuYsUCzb1irb/DJi/zYhlCYQw2lSaD/lFBWkh3ALxD2KVfAjkMzgmHtSeg4a108MzZTuyUQu1uWXJNu5P0cHpu2FOExPqRTfe/F/V9n3b3Okf4wrM53QYZ5Zvv/ZwZF1lfkNcTXe09xHtoO5LcCob926vDL1e1g1P9I72npw5k2oAA2OpXoiybRqsBAqdsW1EnqgeP02VlJBrgM+NIHrYvEhhHyiAIOuXN2oHKO9LQTwIdmSrpn746AaV4gIA3uOcRQ1wLST53tgAPpF/mmnNyejU/w7LQTFiEIu4GSK5L5kOqnELBvZrkelZWqCFp4o8ZROj2P24pBhn0uChh6+9wyGq6AElb+sCWtD9w8TO9oLknZZmSBu8cdgom5aZH2lc1NgsNa+Ds2+wlaKByYDv4uOFTCHH6Dus9oVgpqvTbPeheOmNCDshz7vIFkCZzf5q2mdhY9rVGy9pYj0a0tKbvrfsAlRVkzMMqEptxWGqMTeGBbMzFHriSJrsd6RUjpJaDdKdXYtjsU76A9o6JP6bQiHcW7vpLHNcdalWE6FOvywx2NvSpYjiJ1XKiamowJgXGW/N9msnKqOfxQd8YkScKDZzHJjWoHgXYA+97M4wawsXU2HK2MmzZ5gz81JlpeDmwI/COFv1UqgSrS0pu+t+wCTeKIH1pvCGRWUYA4WdFRz5uQ5GpJfg5q2ZilG+DAQ9YGW6mSyIRD7y/yZHmX2erWhqvJGOR+Zd+vxBjEkLXeQuaeCQ0vS28HQbNJnoglHIlFxTtUFz+l8IIlU1P82klZcfZQbXCPm8gU2jIZVeT0E9gAAS56CLfD3tayjDhWss4eZjcehJ6JCA1Dq15vzdXxb5u/SnB4kCNsn/9lOmN4XSpFb8C4Zg0U3J8trUwf6SnW8i2qHXKUOQ1WfEpj29DmYfBBb+tp/XLWNS/Ivac+tcqjOybwA+JyufcBF4VCZNetzQUGk+a5X4Ug3hecwk68+m//e2SAZ4e1wtedN2I47SUW23qhYeiTlZnem02MePItSX7Q2lgiNwzvZQA/pzl1XMmwn1Pwmj6gSZ5fr/cC4QtfqgMZLc+b3nfPObsLiWXb+s2FYXWeAebKJfZfWYatxfTh2NojMeFkAvU5mVju3XCqpqebD1RxDI8i1e5R6v0U+v7U/7fkUfVfMwpGGjJkNYrsJAF/gWoOgkdYFlB3yFj6LKjXUwJnhAyKa1+SAAPtxSRxwIZf8ldDkOQx6OjrXqgQgMhqUlgUZOrc4NqobsITlCTkTI0dvBOAqSY6Fn7uZJ4KBEvz/L2XwxEjyVcls6Op+SYrLvfdcsqXtykrWJGx65qL/sUgMDJ/ayger8zZY73gQdPi+Sei4E7GAtJX+fBQgHpGhs6vlEFZN6QNnmyzLf48i1JgV/K5jlGYfC51bh5kj9oFDMPIAFkxUgZdDW+Iv7IQ5FfI0p5t6CbnCzH4ZZzV9Sl8iQlbqPe34YOPsIO/hiOrKKUcmTyOgVK9VLksX6DVoZcC6TVqrh4IG0GSGCoo7gEDVm3tlFXDXXpZUdhxeGAy94bdidmLNYrtAt+i9itITuwZq0iwJbF4VQyqgR/NzAAAm7WSAVjKSLWgEH6YERFPMhTyIrd67VOUjrR/AqaoM+bPjCVQ8TZhRipjM1qY2+RwtrC7cpd2qoKRCDh1bVJDmbclWhruySxKvj5xLP1+Im0R2ubgE9XOTh9y4V03h2hSEY5JLKCEsfnwFVsjbV2kzPg8z2CZgUIc5YU/XNjtR5cqGABgoYhz3cCnyXat/UVRqiGl1bFg0+u3fBZ64pLLHkFqcLTwdTXb7YmqU+lZ8RBPOwVNgtKAOo14ny/P7qYn2OAZbFLW1lFZajHNMNttOwyNs+jUFmWWKiVbuq6EmEE+k02ZSGalKzPjS5324mI8tfA4296JTLjSaQbk4YoZbNcuuPokKzTMk19l+1/Az9Y00NMAFFeIkAHVqvE6H8ENme6xKUDqYLLVqFFJ8LjJq4LYk2y06xk7jvmYPQEwq4sVeGpMowbPamE4KwvPzvcZwANbRUp00ciNLjdA8PRuSeKNURqGw0tJUGD5pVOaHdux1BC2uiGZ3SLOVTCfe63sBqzmuVwOuxO4tSJPqRa8p15I0duvSPeqxDaaNLf30aU7xiCydYbtNiCG7QLbmOKrAcyUVODEXPNuJzfrtmdqVFP2s8Eua2iPxpSYqX/11yrjIbgSr33LdpPDtcdkE7xoqQuE4/QvEaf0m02d7raWwhtg9YZSucQV3fsxdsRZfBRSQK7sDpxDG6OFNmnd64NK3A7pHl9pu0CRHVAWXSvz1EMkLb3GmFJYV7xa3aq6eyEflVacKTzZUBr9rqvfw8Sf6po3ap9koPrBB3YdqtSZYa22GEU8sI8c+ASb2Ewl9j3sRInO2mPw2pPKdycnIR6YnNRacvwxXYnWwudiGf2PZtZk2HgBX+mWK75ZBIc+PvJVUee20K1o1911Lp60wcC1lDX9DNh1vrbbi67VM0bN3KQqno5vlvHNd8zSxstJf3Dn02DmDgDcqzKXCjx5BXuUfNAm/Ib49J8WMcRTYFxgBnUA2jE/f2xTjr9eTYUmArQ4wAd9VS2M2tq7Lp8h+1H4rbLgaI7gZJUhEkxexKJBplu8HqK+0lfVuD3GE5z5LUC6CnZcp6zoOZPmTFQ5MllIt1M96TR6AjjSxxqjAeNgx3TzJ2/U64cuCiAaYFyg6rdJkmlAgnCEBF+CQP9D6jFZClrGRKMNofzQPSVZbkeJIFnScdE6rpF/4sMAYkzVC4XykGed/RD/4dWkKhDt4bzEYiwpF8Nf6Q/mI9sukYZFmkdA/f8gkgBcnxU/OezfSAZ7tmlHcHZqbd8uyebA2hXn4sSFgJdmStF2jCzuBiUMtGtB2BafTKkfKqOrlXayuY6QEXOWIPSOustbSqFXm5aWDU+zyez/XpGM7slx6Ii0xZ8zOK+nWyIwbACm+Xzffc/3QbWxxYSjlX5xYRO/pyPnqUR2G+6Qa9fa/QdbMkmGRket5BjF0cgG5RH/3Q2hDArUMifUU4etAwwDMpAcHCAH9fAz1AgPM+Bdo40N+KKLyMIeSfjN34QJ81lHhPR5QrGIsIolpuvVg2s6p0DcQMmc1I7dKnlAi+KyGPa8cwbPO8DCFY+pArpRUJqdCWsQUuM8B5W4kcfnAul9Trx6H1zkB+ayNrGRoi9geUy9AVbBOoKDDgwRO5/5dtjvfHVXoUiMcbBQ3r18J4i3VNP0E/jrRG2P/hvQS57vveehWcNUqRB3vOkdesGp9nm6+je+ZVqUjxdHbBXVDq9ukCxxPTF+dN7QAuV9iyyOccTwMEmHFmpW44RQ7B7keCpUglLO4gMhFh0o8wrA/8+R2InKPHRR+x9lO7aBhdPmGGG8KrPCLPYlJNv6xM5gYm3YyVQiD2yvMtjB+Rz7+TGykrzT47wLABaSvEEeHClUBi9PPzJH9c/ggxTdJ2xmOlGFauPciZbqklIcwoXmt08Nv2Fwq/6yG5c/AOvEsO6lU7TjIYoM1ntNwxB4ji//XpPvFr3vfF+fF0BS4q4OsIVlrZyL6KIVeVwqqNAVoih9zU275ebt3IhWEUHwccE+QqrG7ZMjgBe5AkrkkxsrQL5aO03jHxXhQ6/1A4jzkgGK0fmfGds19y5HlYtZOJNHbDif2gOMD56xTw49ZtgAzhR6YEU/t4uyzrHQWKfBIBVml7XI88XnAHL9NJyS+UE+YR57Mxw774p9LqfZyRBv/1WYs3XKaG9WXq48EfbMJhqH9GK/usZkLn8Ggyu1cg9Vec0PjAr8tB8NO7FVMA7a9w/do7GRIaGkCcMWIGh/BK4z1KmRiAnSjYEn5sJ1GsUupwJruLvg9Z1S1JlpoTKgWDfffx6DeNrR9vLhlAkCB1FMtlxu6exS99j+otynSdDWZJfO1kzus/L2/rHH6ohPzxs6FzY+18WWhJnGNiTyk0+/xMeg8OABkQ+8Ddsnz59fC0hAovPehvtRmBKHeGVLB8kLJVUXTBs9v7Yb1zK273F3C4bhPV8ULJqT702oJoFPied2TtjZmRd7z9MNPLmxXOEyFCUH+QjzN2KwfAH7XVrdImGEj5wQyL1hlO3lwAXr9U+HImHaZwRWOJlQzpFLQc9Fl+A9Cn7dwuVJF6fWacWUYjPKE80uZg3GrcKOGaqP4vSLo8iwlESklJYAOuYaiGGkhXJCH+Ynl8eD9qkDfphnhenZCQRJWzvX7Aqva5umcGqI9saOtdEa6iX/Y/X3Rv3xP1myYZVj28T4P4VMH8gomd7Oo1jA1S9jEjZeSjBIeTevwW2fecqr+xqaKcgGmRQKgsCTncuySKuzVj5o/JeosFxyIFeJ4HjTV91iMl8WicfHbPczlHDHNMawccNeac0dxL9Jy2whre1715F9sHn5gGF+Eime2PK7YiFUiT684fKxotgVpmSaFZ5VTuRogPEjtmY6fwKOATCtql+y3glj8HFz5ev4Rqfr0GAcpqN8Nc7ynGnAv10pzYwByvW+CwiAdGUu3h9fflh0jsn47dKoMb3KjNHSIkH+6y0vlALDDeg5h0OG097mzIHlzWns7F5bKmlg8a6y95egBr3KOfsI75CGA9xOFP0mRXTHwo0wIwEh9FuDIMpM5zAMysui4TBHlxj9cnuMUX0HEAU4Cb6U95eRgNSwuYsoAwnDiaXQGjdQEry3LciAsaxIIL8XTQJ6OfClZWmz43n0S3TiquiTT9ter2RQb6JsUBYV2Ubt+V4m4Sf/Mnmx954Q+Zv9vd9tBDI9gXDFuzYaEy9rRtuOaxELGKFD2XaBF1iGyafih/dYPHQCSczOlOeZ6aPn31e5tgsJm/NxHlrzmnIL6cLoIxzMX/YmAB2psTq72w/cFAHD0zyUj5f9jlFWiahvF2A5TCwYhAsw3+cJ967wIQ4BrkSmG0KjV4F1MxZmDuCMMe4IsHY8q9LtGkJLYwmd8Jw5JhbecFqQ/tCbw2dx/eBuSK48smeYgpRBCI6pHJYqoK3mk02/vYV35cyvMLh7CFnxlO956oyvZhJ6sgceJY0C5I1EN12ay8ne79yCHeLv7XNQL8e5jOxyqolPjfHnmoizDNUg8h2mrGH0tldU3qLljLDcWitJwVOBpMw1PwbeHCorc4v7Biz3rU4OEO7t6j6uqvZ36MQw8QCFNC8CvJqcfG7zKP7nsj8RBMH/PGJzekPVNPgJZ8zCBs5s6HVY8KIdi3qTMaM8/b4GjURVlM/yyEs7EEXh6Kq4o9beqNkMFLMneinoa+8UCAILhbU0L34C8NsOqUhqnh+bnbWb3lABTUTLLhq05Es55ylBQyHv/L58I0LqgG+uLT9m5lfg3htKxtGmFourlhgO+h09WqSTZpY+u+M+GL+Rm23SqZuQhIuDulPApSjLOAAGGKApYzo+IKL1sKh4gBN3nrxq8zu3BZnB+FD4udcr2V7qRH71AlMRfGtEmRYZpCKdzxWSLgOu2g+sLptMSz7T46OLlR0h6UT6tVGTj0J0phpN1mAXMBSrAvA391msCwYBA4MC0P31jfzuahZY7MXVjbE59g/33cdGb+4qmI6SuR3l0S1j3tQTEOoD3hqFYTkHRZReVlR6e20FlNkTgnJ/yF/JCkM+sl0SNH5JmrBE+qvLiBMi2tP1MQSTAH3pTO9iI/icRmjjS8oMCD0UVRSDBq3MKZUqbJPkke3nhsPiyR801nSlJZPM/cJ2kKqMK8RwghciJWMOJzNWNkVbChIl2hIV21lHv1qUOyh2vL9R5fQbRWO4b63/qrNfhOPiIx7pkVM7WhzS6EuKG6qmzA/NjaXpcdU4j2MvJWME1VuyNTE+kJIfh+TXx66E1I4c7zq+JwCke7CF8xm3RJEonyZBiCAxXJ06WLkmEOW/WqDdLFAp1qEfchAiugUIRmoQzbT165UGJkwTP38ygErrJcuowW9yVw6F/aO2TKyQLv333IP5wxmpjts0BlOpWgdZZ+032eICrTrmZlh9Poa3Ndak2XnKVWwmWkDlMYg/ofT80xZ3cLCG15Tbp7RkxfJe2NS7CtaSRGDwndIEFcLgXe2X2Bf+Tl0ZqgymLbE8FnJX7iCFYfoqdffEANG/7zuFhsSUtNjCYGTM0JELZWRrU+DXi0/1RhaqhWk+KnMUMRciviVtkSeDuip6/H1ASBS0GJTdstGA+rltj1B+s+Cdj1oMzn31+G+PGsHmwslIMr2W874d29R4d/CmT6/CYaqwVu4HdTWTHHMYjbzxQlXXk/j5Mr1sg1QgEOIAuCUjx+Zll70waeRKQFlDRMpAqu5VKB2DiJX6osbILurt2q5lmiLR087dJfI7TX087gBNdyT6e1ARHv/hjSvFT//XL98mayJt8h2/9H4powvZO3+Gmp63slXEoggT/q3dsFW4wf6pV3PrrjVGK1N5C+tdmtkvKCS6U7rPmqye0W3vQyVjGmfeh5cDAbDRrpuEV+CQKI1LCTENnlTD2Bl8nDcrn2QDl8fp9I2xlq4a4rL1QkFINYMl6U+YlLfzvP75MSpqVooWhN6Q/h/vENQ5Z+IO0/aHmRlIlvDfXzfG9chkr0YMEw8OkUfzW2ToQOf/dFfARvJ/TEHHaQaeYy+gaoKXdmyMI0OdzDJIAAb539keU0tCYqXNb2SDnOGvab6oqBEzOBnZTrezHx7e9fl5RwoczBxc/BWCb2q16UA5uWmhyKf3pHN1h+cSwPXD9vc4AMRRlbz9pLBtqVpZeyJomTSRy80Wi6O/ot8aCfs8pkeJwJ+Sa6hnHK4IwT2R4PMYeeB3LS6HOdT+jzI4YbW9WzxOCqQY0femb9QC2Olmd/Q1ZNz6zHIX0ueLCSzb6xBJgi8IWRJzWsawPl1fjplR1pRfOLXfgc1gSlKU++z9waRn6DxGXj+wZKTu4HlJlzO6wLy9i4kGUwMgsHZWMtusF4zCUUZJOkfm4EIZ6Ns5EVOVrEad/+KsznUvZ7ZfBnzMSIHfytmY0/L/0m/j3EiPA1+o+vFlGJLd994RUDRaxlQViOGtPhMxvI2SML3ysavf/xCnXQusa62EGyl1n91uI5lXX3PZrdkF+/++mKiu9POUV+6qgHzm6DvhZbg6vgEeBAWKKgAi/97hQkalx1kPbXg5kQV+iE9LFlqVqRCiu5FvPEwx3/P6fv4L83uKyQvpWz72T6GFCOFIbOXBDyZ4bmSXd7YkKub7OW/WmVFKWmPOKaG7uCjbqjWoJ1hob03fKRMH42YJsQ8jmEJ5u6GuEYCmPShMVMrfZK50lQMPrMoDZCFQ4s7Tu/JaL0B0TzdPsMgaKsQP+K/wHvBOdZEgBPbPpNwMZG5SY3RLOyvdF8IQzDJyNuSLkiaUN4YO8fXe4QTP36RzOeYbh70POWq/g4915wbJouSBWWi2weps/qH9NBpOus0l1ikUtPfwy29szMw1WRHtNHH30TP10xBwd3/ozegOwWMj3vLmzttRIzQkqtEtXtXYYNzGXMWTVCpPKRWyYhXHv1eNMHEHbp7gNtFLMeqz3hl3O6AAgdcze7bx3qEn7h97bB5qPVmFBQyNC3DzSdqB0rRTXb8tiew29ifd6jWnjVtYq5iVmQHoGgKHxcoCwrwkFRmLrf0hkcpXoHiNK+V2G+y0M1ZaSEs/Fp6mtAsiW1x/xDH0kDSdDJjQIwdopFnz5p1rd8I14NH4nnzjyWOsQ6W2B18x5rXnRNFH0xVw+OTKNfkG2GVN407SwfNf/e5J06xWYZMpleX4c/bD9Hn/z2soUuDgKRtYHbqKZmiBycJw9DHXWtustqAr2iWg0emJQyL8hOXdOsl42cl/HUIkXaUQljWXub1xiILV/0r3CRyiPWczkMcyv3pGmlEBJTredKTrrCBoRq7QZdgD4vW7taquDxpTNkpQ1MaqnJWCGNZMkZCX6qh/EkUTNmQKuqQopFI1qAPy5HrV/Q7KRsuogzK51GPoQZRTU6605Gkt8atDL90YgD59hS/JInHERxZhNgS1joAT7YWc8w27nPGCiwL6CHqDcr+cZFfmCdJotkJObYGSUu3ePVzTHaHSQHG1b5K9jrDk0NXRN4yFfg6RDDiQnAIUeTWJDJ00A5CXdta9Gyyai6VU1q0b1o3/HyJSzIDeYt25/uYTgvUUjUgn3pPWBQIO5+b5D0zP6TKRxFTUeCzd8P3V2nU4RaRoHWlydiNJRA8PU8M23u6wv+ajrsajI851wVCBKO2fvi0XSH7XTh0wJPfUeS6/qFnj8bvKiUuJZEAjx3dhvUZO1VBWQFUnkL46Ab6pYwjShzmGVrTgY/cpDktZc515OVryNk3XfCIm8E5dN55sIVtk70NSi4/i4CMWEl8Sd3n4G54t2n0PX2wHop8FxdDHbOPlI+y5yxI1dCEPp7FPm86mFEva994Xtz/U04jHp37J9uNIzPhC0Ymah8Uaxcz1ruqw+tNdineBB9R/LsXTCf/0OB+doSbBHJ0EBKr0sM1rtlIVtUL9Vb+TABhfBI8U35SaR5+CDxAj8ZUYFw99FJ9Ti3msoxBzY28E1BKxHCoz8HENFwdd1yjwzH819yJxtSGO0AEJ/5ngwjnibqZjRZL/GInoxfCYghw7TL3A/vMvItnA1BIx7hlDjrzvA58kMrItijJtd7UVDIRr1LtTJbvC9OwZzxUJ+kmrbq96wAy3YXDfTpCtf9AdQZWTJMMVNpZ8Wsu1ubqBo+mfnei5T1nlFjWcV3UNrARtKw0Af0tewUwV7VDg5d0LCkooHkHQ19m8w5+T6KEa6E6HbJTHvmWzJTxmlxSxcXBpBXsnmKqW3nIjjyBLnn7cYJMuX9aOPyymEthLibYffCN2uM81KLHj92wLM5OjEkq23GGkrRW0tBwPFC09QWIEq0ui8niEtxOsgv5rytTumoXg+BxOGt89okjoZrDVWUbIxYePn2t5XN2tgA+TlQq+AVUmU82h9s2PKH/eQUZncO1qFenUce7/FMkH7iKGRwe+ZfPfIDDGdYxibJeNlNOliAGAxQS7lbXSN4ZsGU2niCQSigPxQ0FEpDdzwqTP0am7bQ5mxlZLLmwgRiuU0xmyaSk1GvLByWhHBfX5x8RY72UbK/0fD5GcatO6MTrhjqs7bdu/Bb+96ErP3QQSAjvLxe8a5wgmdO06Q+2EDHFK0dGi+yDWdA+BGels1knQVIrWs1crH1Iw/3ha5KL5ZUhSqWR3kZm9QYsZGjOwmV6T1TDuoV1ZWouxwTgdaZC59gknYEtAQJBaN45IUIwsF0+DcyNtqZ/L06JjEdowUzJpa2OUb7LOTSd9Gj19z08A5PRah83S5/Tc1O8xefm3Tw8JNuvyjRE5lqiZw1zynbh08cl8h4R8iRpDKS2ACP/bPT9ClI0DOw1HaHgYvJI7LC7YdT3+m2FjZHftXV8Sa7SMc3YTjluZa6DhKR1RIYEU6/m7lHF4UjzeYt3giLfiogFWdpE0Lxtxzwg155oJTPhVJmB6pNlkb5UgiXDyCase/va+OxG7+aPqtIn/eb3595/9GDaBMNTkTa8JuN+wz+NWqFG/9IfPcTQADJzOKd5C6bT/fLTm2ZAexorUeXQMzpb8hcdl53/TBhZRoIxEPZ7cVv3v59uPsgVS/NUZCoFNGWqArMbFa33uDexC2d1cdGTyvEA94e4mNKJUdkjSKqyWGUMcDxJwe3EYFUAgef/ICJPkPIOvTVbaiAYBpswjfP6RZLCEZ0mMtXan9iENUsv5ZRAHwxZAayazhBF2ucOTKIezGTIYhzxuXarCwtZYbsfKh4D/yeyi+mUj5NzMKBVjsbbCqZ/fogMtdOnKqIo/u7IEXOGnOIcr/I077h3RTb+mROMO/vslscKhnhlSXY7LOlWUuZjGbGR7fKmYi4KGQrj/k2Yt6MKEesnKgeSc83r/CZHnHp5mgtdcqOlB4JyoUbQXcICISfGtBSHgvvK3f97GIEHb1pYiTX6ep49E8xSEndRSwBYViAUkQoMvINbQAbL8ENHJN2puBWNoUl7ZkTJyqgKhvDQWDg4dtDlG4Gah0GDmEYcYrt4JzDIocZaXlveuNSAgOZd293xq+KxFjF5ehxWe8uMKbdwthGOUch8R2+081fTEEaSeLLlpoTJjnqHThRqo5pSQRIqjr02BDu6ycGNQNVg2Es6vML1PskX12c1MkC/8EwsTUnMzfHdlg2KdTHE8CRbESToJn2QxvxcvbcJo1P9zXINbeCn44fvJ+CQGsLRVIk8HktYKUYjk806PtktUEecTc8P28kPpKbbU6mGi6p/2YphKVGIre7VHcO+HBww4HFlfSX8NOOALGAIpPeun/6dn9cxWiITNiMWXeUwGfsBQEg9/H4f3Oo6bbOvIXUJjoRAsTJkLhyWRU1aaOkGuEXVG5oXQuF6DjgbOLPtEjassJKCd4AKV/1RnconGUb7HWnOqL226VEz5mFtZjKYGsKJ6rit8cSnFqI1Xg0seeVxvf3Q8cqiNgVHHoN0iM04+E4sKegUsCEAT/nVUK3eezlPnzMWsJaw6Z5WVN73fetafA/x2CBuNY1OpXTjfOYeZ7TFni0E/9QTSWbwTazrKD23LSxTdp0nbj93Z81nji7RCjTyorYQcxYNKmcStIOO4A8YKTZGdSDAdqz1jhRxcpKeQLjuel75JFThjaXHnIdgf8lYs5Ho0PXbJK6+SSDYEGYbcH1OwJKuu1FndketCJVARugoxl+AszoAwX+MiW5p0yF0eV20E/otocixxLDJL2YfL5OOSRQQ9yJpeyA6AC0s4XUcbn7fwbhpQnft0YKYXm8Tyqy5QNsbvvZG+TjTVIYkzoagvAnNtw2I5RxoJ10GL9lePegMcet3FWrMz17vRE6ZOMUO5skVkug6UPcdGv0uQsQOqVosJ6U7ss/fdVvFrxORFbUSk2y+MGjKIOnAO4Zsk9C7aB5np4hhnDqQRt8auC6Hv08og3BgoZ02H7QJMk/KFa0/ATzmvWwT6ripXC666MHyODTP8ZW6w1uA9GGUou7raOvFdSnfHNfwpJlS2qKLUwV5DJLEb0Seh4OAA9NnRlP1XweOi5I19SQygsq9wq18obad+mtv68jBkLE8J6IvbAlYacBqvW3sq3um0ujMIZtk7T6v0x5L2+qOx1pLZVh22EO4bgapRMJVfoccRWy+ShmRwg2iVESGAsrpkrKdlKh2tx8H2G9/VWXOzo+tfJo/N5fW1oGFlVYRlFOn+7bZix5JQCgtw/qo2InSomZY4oambQ9QqoOlXjkTWUPwOHsHYUPncFm9SwNqMGXgnoxk+Irw8Nej2jrxrh+6X0uYYGSo2ViAJTj3ezClGXg7AVPKaF4eNcYsiU4WEFCrfrLQdLbclFqk2A93S8PJT7fhyKIj5GqWOz6tXNJz+RELMw3X9S6D9ALbOPc5/YsLBhxSZb6ktu4To8JxH5UXErPfGRxgw46d3KHLoujktBFwDnO4AxiJ9DdYEeVX3dXW8UHZFYu53Whmcq2vY9/j1pbCDzOznyk3jfGYietURim7eysqd4XIG6UUFla3eUvXlkO3UkO0ivjAzRzTLCPLmzEKXWc3/Kmo8/pn7FDqH5YID7TMRKCrNmEKx7Wa5aLKS7UOrDPQk8oIX1imHVB6i6ZxLR789eaYiwvqefj1bSUIAKC1h7H5jIqG4/biRnG0jRj2Z8Dt+4jhA+KyFRVBATlzgQjOgvKEHzGC3uAvSTYCMRblKqt4KI7m6b+dd0y+3kNeveorE8CT26sPuRo4H6qJKuonJ7V0tSVeYFe5GE/PsAhrVM9WD/rKCGI8EnJuh9KGA7CeG+wGVoU1/GO41svOAkW30cqOVPE2W8XVsKZf9hee4u9nJmOuY2qywutCFRVVPeb6ULLVatZY7h/tsxUPtLo4YXznvzC80Vj2I+r2qTaGfVP6uDGKjB7fwMUuTjXLVWFgTaiv7JT1ntRNm5cKh7+Jw9bP+t06e3sra9GU4lGCuT+Zl6X8Xe5WjAc6p7RCXOPqdAPqH6oDzluyT9fXy8Rgfaf4wZKa3gSaF5xydxCf36ZoL66NRW49Z7dFVKpreo3OIb82q+Gew+5GKdFTa3to46BZtS2QLpr/yeAyOmWOJehPeLF3ErUycac0dPOg1bThF6/dHWoaXBkRE22kJy23yzGnuvIxrN0rPt4zo8MBUdf1KYsB8mgenAl/u9iBD2c4u/G8CabNvlQ3Kpah+iuP3uIxkC5Z9y0h0FSmdnQNUAGjfXbDmP1iNNWsJxqpRpQGZXn1zmv6u20e6Gkni8DycDdFMFlkLkgzL6RvQX0PzbB1qNVg/ecWNy1nqKA/Nkge22hzC/e53qrmouGDZhLAz/+uLyYIIWpAea8psMoo2wP5uO1yz5a2+uOkdmiKjlRSB9TbfCQBxZa6PBke79ZO157si0m4FBFsTI4KlG76Zgg5wZKpjEzuSXL0EtNA4mabUMpIHfqbKfombxu0z+/1nupBZ5/9ItE2EM/qVYPoPH8TOG9wO17E6gv6We19bdWAf/6UhvYzAXTupvH1dojrIdafRH1Z3XuyZDdBgWrzuHF0HlNfLUTaonvdU0K3qeeeixluzOMdHpeONasyN44B2qSg8jRnPEDJXmI+CZJXKNDeUbTzeG0c2Rwt5WdIZtHRYYGuccLAndAfaK4pbemzsPBmBYIQ/tWD7IjrRASA0LRibckbXk3pIR6e55dWQpoT5HjPnzGd3hQxgODgl/V8uMRuN9FoR8xYCBpnjN2ZuUd9jO+29gah6R/lnQwMNZEiykd9EIM7NrSGhdzlVXD9HwjyN9obVO6rIxra3Qam+9mN26NjXNstJIMz50uK1b4kINdZCiudDntPmdqjXJYUp7lzZGDJVG0C141k+DlrA63qC5QT92h0+Bmrrxi5cpgy/lEuouBELCyuVrH8L1bBg2uhrKGXtnYtBw2H3tiJ2Hkvq4YpuLGp4iwpCCgrGq8lvbF74MoXdEWcn7OI0zlP/K0A6iMmT9QclSmcIT2Qpe5x0a6UDIaeBx6ASkd0DRGLrnjjbwBnyVWdAOlJKuNzpYBzGPpbf1hy1XwZxJmEINBdnjlZxFb0PiW8bOIRN8o7O7qWYXpI11KBqsX5WfLf2NBAuwkPKhnue7EbjH25ZDIoTTQJ8DUlY4Mx9MdAOp06YwctLULIB8RIiN9ar1QoL/vxBM2wMbTqro1TorYHmTrI1OxVTQE79dJpmT/iwJkMIQWJpGH3iak8AaRmsDElYEEqqq3fWgczEMzZGqY0nqMrIt91a/QWY7T8CgcRIz63c+ip1si7biIFJBjzNWC4jd/Ci+1xFFbmSFtcY62Zcx2EnB5m4m1y21ryOUggwGOl4IvVS/4IUhcZkVolBUVxPA7Z9xwPGkwNd/fSapLXD0qgb2mNhYuKpsxyjowJUO/ur8I5+QL2wantZEE5fZ8aQE/VIJ+6RWbAzedUByq+xxk4oaQ0HvDHOboFQ/Qh4+h9eO9FHwOPequUPAe0mlCiicVxl1zIs4bnVPdpRrRGimRokIBOtGdlmgXJTbFP/Ozn2tEWokDboOiXtHYSi44mPr7QaMn2aQCTMB5r14sKLvRSQeNI2xzUq3Wd3LDYEiFbk1pVAcTWMfUZYRCPm1xCBbCpmWiRQJEc6cMFm+gCFdp+FFyE3xZudMWNXOSCdmYogOh9DrUMRDOyzc9OHiT+HxP0pU0Magl9d7kEv9Z04ipBi1IjhBpBJmFJJoQ3XgXquNzpyaGp8abr4nZzEv0TacPYjjDPoLKwXbmon86pKZqampw4L3sWxB6ADZ752f11RgEJL32XDOi1ZxpNq8GiZI46ykYmGir+Brd+siNjhfcDjRs7mN+GCMnuY42ptmGJ4EXQd9+GvJzfGE9zGHCA87fS7yJstMxmn9hYtKnIvbMxlF2GF7xPDvbOYlPFOHY9a1SHJeYWvrXN81o+vlOYqfPS54aMV/QF9PYeMImmal8btIkcHAwzRw1vF9pa7b6CJUxMP9Y/akIOid4wdjiMuAFBpiS3RJDVo3hVu9SAfcaj9bXDifbWQLyTSRQubRraXn1kXgR9IFmFPCM8kFkLV+l3USJFkQ5FXI2srOfPM3hiTRBs5XMoOgg2NkQa+Yug3wgDb5HOuImSOgkBt2qTjMYjcss2pAyrdjpdCksTlycpNeCHPcdi7zIg05jWkIbJqQNCvO3re1EkbpTnTcySmsl8KE7bgg9zgJRkvkipek3r9aP/c6W05D/KQdKsdJjs3Q9OX6gIsDWnS59ScirLYwyI7vMf/fXtd1FQbfV8McYie1vXHtFvKIbRYtC0YrEnzapLsquNIjkRS0hOim0E9JF46ju+tNebd1rRhwk+C4XtPpBbeIulBbxLbIPydu1v6yk7ooqiO/VemsRpqmJuUKm4jYciXdCGYR+nKuo88eQ77FPSq6Oc7kp7SYgcd9S6pVVP1j71WI/3lEnngczA98aIQZUfw6220KFx8bT22epEdeThRQVCwjjm0IDSKr4v0Dv/5+aIuEfaOkY5RLhs3YsIJNi6nwdSS8b9/cym+xhe65KbgiUqGspWzyamtUGYPrEb4lqS3DyvFYi165/ogMuxgknOshXsfTJk/iJ4C7FLjmrv/7e8I60LxfTmGylevnI7rBCxjBSZFQ47uZ2vHqAp0/CHT0LAjO/9Nji296ikVEEo4dXDdVpZjvWEQQUVvOqFcuz2BO2KSOYMQVsdC8hgTJ2rppTQEE+miKkFIvpyzdKIB/hfdqPTHbxX7aVa1+M19HApU683ykRpVlAKPBPvve6iJSJqw9g0kj8T915YpIFvbqA5ySbEzoJRSApALnJ9s2GP7C64MnrHDeWDt4gwXTAeBKuK8Rh1AxowAUty25dsNKzpbIwrq6AVAKbTQ2LvhSFDOIhZw8aCfjX9lpk1PRNVQvp5oGG85Oe4+czBpwlgSqAo1L7DE3+L7SE3Pp5TF3rUo/ysIBJ6BvqUvBH+gK/p46q3xkecYDPOR2HsRJlk+bMwkfVYYfGPAXY8pVyaSD+lWALR/SKdjG+BdEWt0oyYGNiJpt0hWiGgZNhmTZ5du8R8N0ZZ8mnLpzbczKZrvJ4ZFseFW054hOErMaefVWKInOkGIVZLC0MjndJ8+mXjgN+R8uL2kAf34gsbHOxqp2lQUB7xl7UCaUtajjC9Na/df/R1vqy5XoEDGq9B1oM+eMKRwKqhxFhHpuqQ1bWRrS3+zX5srzybeuO6lq/8p9zmzXLISdiRtnwNF2ZfHpj/0nRMFC2WF8m8m44gBhCrQWLrb0Aet52KFOcwdPJG8sUtIuPMWcmM6pPOXxF9FpEJWY/kskpcJtLUGuhc9AoPnvoNgYxkPPQK+IfAGhCwLPVmkLdlrmkovXIaKC+juxXAKe9sGtZaSW43UPLxADVRicfJigwzxMaAFLEgmtc/H5/jf418QUgnSbf9Tk5xEEwh7Dk27d/hHLiHu+wJDbl70YswbbpA8zKFIl5SoyW53qNXXHKPiPCRijJuWULDaZQIu0dBOqB2kZlsiDHHfnMqVUluN8QxPf5kP10fhvf/0K57nVu21Am4YPAnBaJm4raoRmC+CyOoh46ZKAI2UhPOmhrETB0hCAXU6ZawJrR+2l5CWlOauBv+6lgy8muzGljsn/l8xvc7NkXFmTdW6kCLE9HVf+m3rZIjXLYcnLLKEfdBvhRNGEeo+fxs3FIZK4i1p+MarR6dpzsysemxkCkqSNTRV9NIYUgX7mZnmOpedEDe0O4TKRpXly5VxYke9jVfbuD8xQAKPSa0MV3RyuwU9KWreaxCjXkaGZBgiyKPG4OsuE7KPr4/BDIUXJdsz5w/VIXzz4I2MxGixOYj6Kkcz92IxlQjUmV7aE6JS/CHT0LApoohoRs3KyKc5gtEoaVnFvGlZdTLgbAykiJ0ktuSt14yJqZ8V4zR2OwRc25/hu71bmKappZOwA2sioPnjkI7gZjW6OOOqgXqU9vDfOACseCwHPEjzzjt0T46oo5c25W/ge7b5vK/PS04FrQzKR03ieeoDhflvQhUdYzQtaG1OQGLC9o4dwJSKNXVLknZ49DmtavBtekr83p7j/uzwXJ5pzrEzSYFip2+NTMDVpV0eZY6UBH9wWwJUix/Lw3hbC4ZceKFl3BT/xQF5Pnpu7OT9zqf0GYPKe5tBwTlPFi2CIE7yFWV7aMhOVpcRsBNeeGnTvXmIa1BSa3r84MdekQcNzGzDgLdHqQIOgEAE8s0FKKOdInMYyd4efJKqgEsteiC/kMBCn1iS4pQRxV/04kyGtuyBBEXvvj9lkWl4vChbC8ToN5G4sVZVYnbGZCBkLfFgYZTJjPCEd8bvDeAiW+ISr1jtclxlACPGXmJJCvFZzcGWnuGqhOoOzJVMjnWrwQV0wvzCvDCtHWmiSoFzTu1EhLwxdCmP3Uhfs8K+yrjTKTDo1WMsRz6xILAVI0T1TWJviaQTjzPngBtfaoDhUL7iuxETro+3DnnQev4zxO1x7nljLcBSc9rz8twFW8PHmemezn/ZyVnSz1B6IJCrw73yaijfrD0DWhtaE9CG1TpIffW7yQIFNlnLIMLhvmdoYyKo/JYz7Q9cCgvVzgdLZyPcOkGWhDDbF/Z0Z3cFSvZf73yDPXVHGBeLnarqxjkkFFID14cbqNERJ2thbk3hG6oOGb4AYhrsDCjhcx8hnVFmTE6CXdcFNkMiAp8NG/uYXIPK6hsXc7Xuo8rI9sLEo1wmQ6L+TgtyLNrTIbkfqwP7vgnTOOMFLkdepoOj9efPb06f93gw23fLcz4ohWXxr3eDWlCNToQEOP9sQ5jc2ERhTD3Xby1334hmx+rk64Tsa69lQlk5FE47xMqzAEcusBDkJ73KYBAc/Dx445ezgM6ZnkiBJuAK+6ZgQyhSkWFgnt8ydH0Jo3jQs6trR+yFFQSfpL9E5OEafKI2677jfYdrI2rZrmndXwQq6V7oxSeiSQJTBhZTksmPBHJAcM5R7tEFwsPhz9yB9VnERTYPw5+O06bzdRosNZcTQwJdGBL58FGPRT+yX3E4Tngf+xp/YCt+AbyiuiMG8VD/kULldaj5lnlkqSC/YNX44DDLtL1OQI6tVE15eTUm4ahFC98rz2DPBtfRs2SLSykLjZzX2qwqopV69MCIfxNjnWGg7vJl+zzIRxCXhyT73y9rmKxTBCZUjYhB701kOLnPdiDnLciIcEgo/fdpTngZQqSXXWxguz+dkJJT8tGRDcgyKJZW6Eagy6DqRHD9n/zLu31+DabZoBloSkQH+eNKjyq15XCZS0flJQxNS7f0rRnMdy1rfoYWeiKRmzTZKCgRgXWH/y4alGDZwqeC8zQvx1e0NoLozsWspaHVYfcQMWxnkvXCkx0mmznB9lAMUxHkRYc8gxCRrwUC8A3L/xEc38DnStu0Yna2NOaOLhZmXylhB12pYAuzPUizhVLXtqzQ2mbU0DxvcreUcZXKl+3LlgUylZ9lEUUfW+cD616xRm5sifn/ozjEWM6iEBuWyVpQU1hHGOKeIgV/Om26DvfXfUjGh2VfGS75/sBOjkkIwea2uMfzx91xaGVCCPQiZQCaeP3akiw41Najtp52Gk29jyVXsCqL48L5EbSKuCU1WsMXXRBQjSHuON/HlVWxjePs2GEcKAo4eUf6UYA313Dz8SbGGj8YyQxYyTA23vXzRB0IDmYKDAjnB+MThTjdqMqblANwwuGe9mvOATeTUw/tcBuxpUxRDwqV5+vBhpqPajSYOLFOmyqEOGciJYSaLRDluQN3xPx0Skcn7pWN4h1CkP4cKDbVpwARCGG42mYw57DZtiIVXsAbaT6yxFKUEDQdl9BTb3my5U89DBwoe/8eCHOhGQ/qlmfepze6/EBz2vDHEPJjKcyvgJDUK5eCySV9Mw5Z9qdKOMBgtUsF+npiMul0FPI1VFPgC0drzhPFLf1hnQQPNilgjrETcZ6VCzqxfMxNzcLSTxfzzHt4c5s+P/UhyeOhjdUo6ADRpQ5ydKZn6CTHgjlYzFQ34PaK9FfeUJUYwxhScd1vD2C3E0uJrKgHnip/LQwyKV9kmNzxIxLUwXtdCERf6T2EBk7PyitWU4ZaYQZ0oDqJE4VzFlj6Fl3X7bTriYkhRKyN1tOqTqFRqEyHb8X4HDstna7lkDvBJEHZ9A2ZeTOXZdMvsKLs40OyR7RopueEGoq2mR9v8toZx0MlgLRJXl6mbEsbpsET0gnwa/xLruU22xO00W+UV7T1mUtu5XuAPVnJNrRQB7pAOrMwDOqihSNBGxOA4uHWhRKW0PFt3/ddxm5uOa7uJpai7uXZCbbopMEWVZoLlyHHoXY5mfKekn5GyGr9ju13EL8FB00DhMPNUZWzR0SVNTF5gMZUU7NEEwM8yHkAMqFmUjrVhDcOGVqUJtz1DXKC2RUtaQYl8jKR5UruZGBanw9fu2oYiZJ5LGDEG8m8sJvAlOAEhMhSOH7g4HuV7nUqvzhQbfzY8tOksqm7pi6uSvQtuIPfmCevTjXcqBCQ1D36DeI/ckCvrhyW7qNV2h9Bphvmg8YdxACP1Ne67PrtqUsPxd2mZvULGJ8Ehblq5OniDNH0ftOxU4YpdRDFoeGh1RaH9YtYnUGyHqfnze/MWF78WxpuTJcbAYthn1wrNGVkY4KAa+lwBEBCDKg4OWunzL2mhSvbN9YEFUejYko0ZusANh92nhL8v+DWdCc6TfahUATEOgpLp1q3F+AT1zO42o52hgO2n4OvTE2y9+nWAA/UvlEQCfrdvQ1bDkzHMsUlHG+e9iX1E8JymzazzRw5x132QahJxV1Jcfdxfp54wf09hoGRd4S+ZNMS5ERphSF0f7nDIC7k3L4VNBYp4sEt/GagicOLBK44nZ1imwfZbKzmvWj3qVnqrx459BoubUtMJpHDE4nLjwvLW6RanpNwfHugL/gm51IHdJpTSYw65eUa+0d1X2ItdCO3ydY0o+E7htYhDN7mxwDrav24+v3UIrQt6jDbSyBLY9KJxb8xDwbDC8026vM/I7bdI869Oz8Arxg+N+tOnlru6eCCQsy170cR6KIW00y9u3BcOquqY4F9nAdltaYAGCScyGbgg0pkuF9yi481MhB3v5WKenUIFGbkd/hEN69ShKHPtFWoxN6dfyG9iYxBfj655yz7NfX6GRBngp+ABkZvItO9IRP9x5az0VDKU2cAscwJdzMROYbn91XdvJukvsz31qvyesjJZ3cn1JnP8cqtqJ5eK8cm0wWcwMc3/ssj4Si/O9m3i9V6swpO31WxVBUYec3RYMrKEguHgvALYkUYtyZYS+42wKVP1LanfGNrMNahPBR2AT3gLuN5tS5AAeezTgeRfZb0S69uFuNSYXjDVpPf2fEfYbkryTBYVxtDROxD6ATTyct6ZbEw8zaTEYLsXqT6yRnOG7zCI4nCOxgujldAUwEcpX/i8qfq+PppbQsyOkERg33r1qtgjEQ1Z8VnxoWc4CznvrnJkwCuufFfjDxcUM7wOuwWqduTNYB8+DmqEPXTFnN1ro4e/UgycENlFGIb1tsM0f6LEOtVDnaZ1vpCyS8wWI0PpV4k5Ljv+wLi+PH9hvvHagBvwSODpJb4dcP6A8tdD6UEg7hQtG/VkdKL/SQUTS8uOYjJrhi9qij6nkzj7U3fdJkLx0uCAD3+ODErwu3VzjfH+3Y7pSFZPlOSqWgqVGiD/9YIaMOWv0HmDzyd5qcdlhdRZyQjHStVVb2epsghdFDGLQ0LGjTyvDw1SN8HqITT0bjR5zPXXEADCgb8QlKBowJHKA/HD0GCU46xIE+is6KBhObxvODB6xcVblD+WiCyO2v1apKjPogYmNyabLBbBLNS+FP4rR+5/BGV5lkBGLRx/1lE0YR100gbB5QiEzFSDFoHcNd+CA8zVmdAIxvLeP9+uw+7p9decKGP8LaqQegmcimgq9kFvxr+QHwTxj2/NKdTg6pJW7WaanQtKf/fZbDJB/5MJS4j3ut5jevXXdOipsjX6sWVGhDHPGjzloDaAYMAnupwc1i9cmEW0LnoAn2SWHg5MH7usQZ+85xAlpIilx4EGuk8vzWnqoInmkhBpmCpyei3NWaCYberZEyM23RjcnbKj6+p28rrjD6y4PlpwWCvm6VGGJK5+Ms3CfeFluthatVhQ/rMr9ijj1JNCxWyM4P8Kc/U5F61UhLwi4eQLJjaa9Su+/DaxJObNnhUqtT5Sv2q5PVr4J3u0HpB4VnArWehMbNdJZrzzDsQQgyCdK4GBJIotxSDSslnSGZSG9aaROfpxpBYzpPDuyrEhmGrfIdlK8yDhajPXtsOT9LnSsNuOhTtk9N6WTfnTWUE+WJrDVdbEsAkbsgS9/9JCxvGu79IfwLVV/O1I1Gb70K1TaEfF+vkCs950cufSbgvxQl+KKSarjGVNPNKRkP6E5rgNK389LVR0escRZyAIQBKLTa4aLnMyycsMoscXv+uThKlaGtUbVI4ryP5eIAiXZ6BPGPjIPRTbJ+jO455/MA0h1cNhBiEqBB18p87s0iDgbNVKvyru3vv9vaTynBhrT1z3W9kLqnBvnFKmvGeTDFQx8cBKDzEzcJ/V0VXbrcGd8Asq/AtD+uHsvrFakbQFZVLZM2mQ3uCQ99dVqMdMdkE18c60LTh2v8z72iD6t1d43bzAV6jwGBheltbBZ6HH+W1RMTCGdftCHa7bct2K9WsWEjZ3XBzbvw8IF2fUwcMUPaC7wnnfAo0vmw1EiQMH4fRq25U5Q+BbbJCRMSvmpaGo+8p7PRvgm5v922TTlZQedNakAY6OBxqgvH2LnU7CN7XXNQAaK/YBzJWiCfG/vO25c0Y9QD+RgpqdRX76CSyKO4Mg78P/oedQSgvh2Nzb/AQ6UYml0/rOrQUMn+qOxqOJf5PHkLqD3ZzCvn4+S5INZdwjcHEmIk6qVHP11EO2QclvSliomCxe3TgYasCpadKIgIZxdMcqRVZln20oIkmh7gER5fXyNNpNwF7gGW6706cFh1a+oNZzky756og+6BfV6iUM2E3qfksTqPBrkWK29fllQir5DQ7SqL46h3/B9tGERAfdZs511IgfcoSzp8GfoAnm6cnD6e1198rFfmRUKXJPP4rMpgrU5XfaRXY/3f9rOLl2ckMB43ooUP9B2CyXphl9QazDa90OmDGitiNMHzanYVxcn5LXaGrZS0EqZmIZlvifchPsVRR+g5c4fQErN9ckp35UP1oXd3grjN11zR8BQgaiWI14W+HxzSEb4YVMQCW7lJpqiVufN7dPrRnTK5zopy1sqApbYx4RIAJEFUyNp9HnBuQG4rhY2aID0sGHB4ouf2j0IrvVszK63zdgwQTrSkM6ikgG3qnIbqiu2V63Vg9as+Yns2Jtmp1nq0iAh7kUu8tT6ueJaNZpHFtnl828kgrk0yOhCSga/Orz4jIHGzYjqM/grBTf0ukqJOV0ZQLWMxC1BnYmsyVr5njglG+uaaa5ORAgdh6mDJUSDqcUGk9F2HvDBVn0ylA9oCC8KbP06RmGgpoXeuE8S/ChB7eNUWSM56Yt849f7+yHV2LfWFmwZZDeQcmJ6gVrCC0wocxKZTsXjVLdFDQbrT75MnEmy9TCRptveKXj0HL9WehqeqHTjRZyHjuGXkG1/bKqSsBM2RaxwUav9xPnyTNOsvnnYnuZIm/btGO/1UfayMWweKWCNu/ke7bRrqPn9f/M08ZS+SRE2k2xuU/ECS+CptBqvHS1cPc+M8veonCzXXGO/nzKQ9x6UFLWGgjNLG+F7Irje/Xd1uzNuvN0Be3IP8vBwDGzpwzECDCCTz8S15vv35X7FgBiW6EQJ3V/sClZ9WsWwiVkuB0wrI6l/KTz6bjxzd80WY7IPluji8n5y0Nv/I7XUughuZV93Gly2woIYiofOC/l9KR0+wd1Z+ckJDUitHBfLOcwhnqedFdycuoHGcDeXySkgBXf9Mj7YfFU1gT6VkZVr8EJzcd2AISTx8Y6/SeRJQK2vlLb0/QfgAvle0IE9AsSbkLquNz9wDBHhTDQ63XhvJmrYSg0LrWEfSe3uRmle70C+B+ksrNu51guKJ1wg5ZVQIe+4vNZO7DoPhz211DaYeLfTBQ13QdFbHiamOOqcZ2ptCp/lrqTB2dJgl4zHg5D/y1CpXo/XHYs7SWMsZT7xkoc5WTyT+EqpjykXl8k2m4xMK7OZZaRS6AX8wGUeleNqQ5Qcn9XmDytJQp06ByE3wqCqsJk5kNFb5CKpdLa6GYH0oHBldqCnRJS05pznGwjG42++uvb/Ciyq+rF+o562eez5SeMrdVq4LP50GWbl+8W6pL1/VxOpvJ46B5ukOOqtxJn0xBZAjZXn9entgPpSSwPSEm1a0KUW+DOX5FyTP8cHRdFbw8NRD1cjT3VT38YTrhMrg7qsbzBJsWTuUj0/VyNtTdAuIzuOt8kHSPjYGjG3qEdikTUD5BqdDrCPqKIDTGkQCzxfL0FkOD0JrF/p1v7+zNuPtCirFVqhRJNDW4a/Qnx+UPaRmn0uE/XzMP+OcAsMo96nIpGIxmndnXr1M56+ydhI8+ona2tPgq6zZNAhGsOtUWRcBwzGm/fwO0q1cIizFVir4Kz7KvY01EKbZKEoplxJv98HPMzw3CUtHWd5Y2g2318Qf51etrID5+PQnvv3fdBmgWWcjkZcremPtRNA4tr0V9SpaupOSWp9XMNbNkmcKB15Du3h3qhYp73tEXZ1O3MPmSo7CA18O8kE5SkhEznG8Uo1hqetZRVQae58I/VXevfeKseLgrQ74xSGYWEGOdZE1g46gIKuQcMeZd+/hJJdX4wnSNuIyLDpHKv7tS21tuG1/WZRG04NvoL70fZUHtBPnrUQVHavJQcIszbYEAdH+4z8tg6vlyrCGKRowS+DBx+VsfKSheSHJhBcYLDXsnQLt4nV3L7UXH7Os6negcGNkmwwQlMdnnAQjlLUNPM4pi97zjHo0oiT3ty2yf0pqDk3CJYUolG/ed8BPzPZW1IbZgmOQlodm+Iva1toP3td/eDwdS/SzkJMSKVcdr42ue7LcA2/jyWxD2CCEAgGmioTjOTEghs8nnI9Jpi4Gf8WD6a1WvsRfC04gj2pUNe+K9EXAlLLIMjgAmKvewLSBAkgEBDMKM34gS0+vbZBUfqr7fwL58NQ1fzNuPIdqv+EJRHtKEsGcD/xD6ZRnprUg8vdItUn8UtJuu5DVzjMmWd9ESOFhxHUj3kbhdXSzJLG8flXb6WK48m8YY8mXjaTH+IaoSV9dMFoaJzN7SPZ/sNFg5QzzI3dptYk18H+TnZ6cLkPiXjaUp4hDzbzT/oTd+1jHnlohibVkpcYZcrlGsamWIhUqBHxYKHK3QSlobadwck6oYcxeWfwxdCaOHly+aYsT0gMrjLfQ3xAYHrr1bo0WM2kpJ1qHEls9gLhUXwdHYzdBUUsbZxACoj0WSnRQMZ/n8+fZPvB7+WBf+SIHFS0r5dD7MtHw6KHf+X87pTlwunKmDUa0gIoS4VHteU2JAB8l+ALETEqP7XNUZI26w2IShGHX/lRo1gH2ScbJTh7rTewqiFJVv1/Rn7Zx7nXKu9dTOicT3X9o2YAFl0Dsb7vAWAEMdfHK15NuvlguTVMYEZxuRXpeG/iHrW2LDe/RjgHAnKu9zXttXqKa/NwUfslpbsOvXxhjuUUB4T1gUj5qp38tVh8DSpYfyOKJy9KSxoGpvCwhA+4UaOcQZS3z8PkvSKt4HReiqtd0HW3VIVY8E73pKfcDHHpsNs6pR99o3mYfObcV5XzruAyClHDfyJuTelTDcXVhfkEgV02SUfyjwQPaNDDGeVoziXuSSxPY8CpaXnXcrM346g2yiHjXHvtyFg/EZmkWpIYGmLVsaeMRCpKpT81AuhJPCMqBtYFCHeiVA2jnnRJzvldiOTTX/UsyQkWdtBPuY9vwxCwbcNm+Tfy7sWIPD//S1tlH617AXRn0TsR/jVG3k6zgjTs6ydDbTcuoS07bOgAnQ4zXZeK5gT7/MKsv/UEKT5gw3+z5gT4Qjo4smb4HCktdZ66WE80MjovmFVpJP9EozyL0nIt4lt/qQRDylwk/Pw2nfUvq927ypsdIW2ZZ/GHOL/ijG00KzDcEgT/sNWYhKUeHtw7gljXemiI5ucql537EvPrVsGjCFvW08YSxN+8sQ/POpLhxArg1LSJF2Sz8QVr++fdYQTP/piJEYhnZcA7rl5Cud5I26nWR6u0CQfYkrkYopfQgCzVV8BiNsVXXFgWSNM4bNkCJ6bUi8UKSVLLNNq/ncuToHwqp0d8Vk88UVCz7RDC4CBKseeOIII0uW8RHM70i5uKvoHyIKq2qsLmLzVMQWu+pPu9HLUWJYMTVPsLP846JbiC1kLrR3XJflzX2MOtW4i90Yz/cTwXlItk/OTSWQ1tHIZHeDxuUvev0tPIf/fxtvYru8aXFyO5kwo2lTCdPG8REp/+GS1jZMFqcXkGcBvwEJLv6bedAheFxVIFvggBip/vS9wJKKBp2Ibrc3liNy7bVF8K2P7XNeYR8l+JJdyzm1cZVIrRuN+yIEo+nZiwB0aY5myZut08K2qF6W+uSSUGJRdOjliZgPqEKIlEFmv2AWsy80stgeP1sR2ArBzb4XhJ7Gz+RYYnOWtTp+T311cd+qzE0a1tOfvR7i3jUMvhtQGDwMyBnZ0NGkwAuj7he5yBfN3t1yoqZ7FSxz5vnbOGYkIHy7DzZAGnS/sYzq8aWD6iQNa1EKIkHQknyFiFwcliI47QVYMGyRxj9T4BquMMIQnIsTg7M0vYduA2UQFLfuqae0ZrMPL/At+j3Z+CsWG6NLx8E4DlDskPJrbGRtGkmJAKXqyVt9i4osxLxIQ092eEyE4ZjEI3qQ0a6iXzH5INfM1yQgWl2qMl17sgZOBO/gnY/cvIzqjbCzIOwhYIjNKUEVPeXtu//woHC7dFkpH+EKLFn9hqGzxmhmYTPrCd4KRX2SNGIpYzf+jJje+ZQ6mIYJJTrbobA+EAY7z0Iqn/st7Hzd4WAhu/rDFHcaSSqPTQX3Uuu36ekAd/+sadvurrnjLWlT9c2To9Pm4Mi16UMcLkSawO7tvoIsBEI+9UscmkMaqRUw12SuIf55KNVBj53e3gK4E/dZjN5UMNZ0XwgkvuYT4XARIwhcXM8ggN3727XS2GMpjvxZp1+WP0RswMces6cEdG0V3oEH+32XxiQL2k8WNqbImBL/n06j1vi5KGi7x7l5ae/GiwrCWRmR2K8UP3cI0cjjHCvPiEooL6dThM4Iv9aQGVxLNxUKhBDt8JqYKsS0hbrETw4+pq092lFLiBEKVgx/+rq+A8EfWbXvDmHHoQlCyqyTSrXLHzIQJUok7UnEx8f9JeJnZBJv+n96ls1yLM6BPjVeXT2YnkEM9SWsztuNocf4Pq8k37tAKfmQYEPECKOnLCHLG3TFWtA2rd+HIruOo82qBjy9+nLeJlOa5XyDBYbAIvwK5qpA2sNWq/c1HPoNrQyNdDocPeVSJhgGrQBRlTM6bnM5YZ1vk3PzocqkyzOwEpidxStOiynSwbWwx5u5qbXBI091dPh1AHAioSx/UeITFZ3nZ9N8TEbGpwURC///bzPe3Kr5uxXElupV0w4o14Be0A/ChXzDAdVA85eyM2EtH7roypLmQDqx/n3++oVYkNbZMJ6g9x+1YSaR5ITO7YaAjtC7rfvUkN1pf/xdo8p+MyPT75IfVFj9imEgY87tzPcBBWjIGpDFORCW8/R7OW3kLhZkSBwTD9mOpqaCmn5maWEM1B4t6dXo0igvgWtYxCaalzndRjJCBsin+WjOQtfW/0UGINnbBq+mChfC5UykhcbXff9wtxLAqqyNAUrp/aqjNtxIP/LUTLhzj5+p4XdrtQumQqjL41xhxQ6SRjBigjNVjRVAAyW0zMqP4wlrwt0xbPg/mO/h/OelKZOKVEgS/k2VWKYHZiMK2LzM/OpC8L6eGHfdCfvLfSmmCqHEZRilMlBjqzuCFoZAJqFY6j1mhzrIdfLartEbNDbrJp6J79x4JwbkgQR5oRHvrA4hJ8Va23Bk32b8a8Hycm0qKiZv/mW7+PxCxgNPceyYjcIs4qzRbXf4z6HYEChrWc3OUTZw5HHlmG3JiCcwFTH2kJyMBaslzTS2AsaQgxqkbxQ76dRVIANyFpapwozAHlget4GrOVzJxB8DMB+4yco8CHS4i84K83e1k0LbVI3wvoSZFofSGo2uRUaApOHxZCWMXd0Lg87piEEkQww6MiqLCqrn6mub4enISoLaj22qOnP1nyPMfw/b5pZfLV+SH13dpyM6kqFPQrmLiCht5WB4/z+wOqoloE36bhNeys3h3aMSOer1GoEjWESopkIuO3j/TLHKj1pSMGnUbBukh5CRCP08PzWB0dnBQ4d1INQpISvkb21FrrhVhS8D9jizsPp5Reih37XkzQ+LBmn2jS0As+JRdNWAYpPza5g9JNlFe4d3DXpMScofqAJx6SnEzBIaqOljrxUNUSOOBDtohV/aoyhNjmL1iqYMigqqwk/1R5ogh+Fu0Y2+17gOzIhcQl8aXuc+raOJKe4tklxXRCv6ZyQhAKLrHMAzfdShQRdOILSzxob4ScozzaktKG9q6jDmd4A1RLElGrFqReh7EG3YAir/LSYX4D9GSKU5PbaO5gAuhMPEyb6/4r5V4QBA0Fo7zU4tYO2Cd5NpDp58Fx5gk7Ig/F/pzEXQ2jIuI+7jTyB3jG057PRl9RPDUM4/aZYNpCQ7miOlHwjCamUS0ukNN5+K/NdeJdkFRMbRqQhqcvPEJ5/LLw5zlFx8/H1reA0kM1hhBZdlDGUCOvK3vPMC63lnyfKk399wuH4/sLNqrHDr0TBjmQl71jEtrh/hbS/PE3Jpue/6gvOk/m26rNxE0GspdLTe4aKcdSwTmB7Kvh5UcEw3pLy11JRGV5g6ewNGtus1zNlvFgTl0SWB1qbI/5/WSDBqMaAI8BiJ1TVUEDeNzAsOBqugWgrk06OauD5PYMtGW113lfVIPA5AL2KKCIN1aI1EFaRzZmCzzYHwGRX0WL4QE7db1dPwatGymketsAtTq10/hQGiZq5XJ+bmByEfZ3OQWYXyW9iW0FqqvAXU7hi+1uD4IK1AW56g3xz/YEqsrVlu/sxIM24Q5geYk+ScgtPV2eMnxhP29LwCV9eolvdVMkn00qDczT2PJY3fGZ3MkrCHq5XWRF9lqmVcioj7ZIN+KUdllBe2dYgC4uQEKNgE6MK4p3hKkiClsgZprPor60ir9h6Rsu/TPumdKTcBL9hGjeKl9ga6+Op5TG1O+X20czbiYmhsLjny4//PzmELYYV1vUQeRxSl3GkZWwdzSBDcweFVCT6eM/y8u5gbu+fM6lQOtjrW25C+9lsuBcGrhfzGWE9TwDWhHGQjxI1I18fKhhVyCZ2RS2XCx054KkrHzimFfZnqZPzg2C5CikN3+QP4//vAU6Z4IpTjdtmvY0bJgFwfeK+RsyM6GVNi4fRuFCAcs5yynS+2Dr0gGd1bf91pkqs/3u2HXgMxwVxeKIp2jCSiiLZagJusYlQjp9zCumAQm6QeZHOlpCCJZ6TjTBVtkFJMuadYsQBCmdqmuDmuCygQeb3aqy8eTzgk3Dw0pJ+HQKmYgG6+anSDdI/cDzod7R1yyKch0lCdljiIDYVMGdTLvE9T5uparLdVgFxpScjsrq3Lx6e/1xEI1Ri3ZQOdKGrhh9ppJVz7X7YQGnFZDkZEvJV2+qoRmQ/tVPiQO4KYoL+p8VSVvrvcs7467p/HXEf1zf03z2o9nFwDkcoLsbfG+HxtV+YcMBHOy/F9ngmiqZI/PfuRi8mOqv8upoP1rWiZBWTp8E9XTV4Y/M0Fk5PXMBciQleL08OcZN6syBnD3Ol/o9nVwg3JVtYkQ6MNdoVcNKMYcUbcGcD9404JpVfhYAopsQbWgjC1fpogqKrQdmNTmt4uhLlcj7DTasH3VmkeN1NBAWkCMbj7LVLDB6c8YFHRBx4rSiKqn3YefZXjvqrZglYy68TKEPdrRLQs4fVLFVOnYggJ2SW9hqpBUZTDA00lnTWdmxbUXNp24kxk7DLeFQN35vfZno3IA35O348gINsNNKSHlIGR5ZzgnoPx6QqmRG1dKFSflsG372yC3dSWsbPogGJGjaooqLe++AnJMLZF09pxwlac8klId2Tv+Y+VVItKOUgLwY7+pO7h3U8vTOk87eDRDABDFRkBSEtbH5qk/5Nade2O4UiwWoReZXSpbIGTOo+d6mcPfUSlv8CvNKEpa4OlL6DlutoiCHOiTFhtxgwimoYX4E0uP4hzKwQQe6RhkIEyRsHRx9tRbQWVIwDu0fgVH7ImwUSm/FFpw0VFMXrFTIgeJL1DTbYK/JJFHuYUC83TwbL0UkLg9NPnGoYAY8jy7Oug+HyVGfRIurQp1RccTv8ia1nTeoe9fZjTgVnVqs+v9stHCKPFICUklFvVot/ihdfKo21m9f2uHSZm04wQ6sWV1s5E14MFsEQw0IpHJULksKALWZjl90NAtcpLFdl263PpR1UdMH9FtijZQMDk3UHSC9H1D0ButVLk3LQ9cYe7F7OD+HM6H8CZ9Hk1oT6OE+xbRdEnuDibjy+KalI/L8Z7uFJa4D91KL7zA12f61aS8J6M3YaFiNaEQ98xEtrUFqNc6FMKDVpnPaXn3HgxpxXmSY0jFfpTmtGCyLegpp8TXuYOiEg25YbcqEVgWy3jFVRZPs6tabdr4UKeG3wWxBadK3XXV3+jSmTJrQFt5L19EgfN+9SCa4g4pjUknuOQRex/FL4066hoi0EfjpzpSyuRZ8RJZWYKF4nNdGxOectBCpoF1NDuc8XCUaGoO11NF/4gjrVr43TrVBWm84jxjXb8sjAjqk2cWt3S5wSOQm4bFJ894rNvwA3eRNAoiH7dwHLrUYp2hWAQtnHRGmzW+Ze600Ec+jGjPZI8qmfVWJX0YvxL1bpZpOy141D+oOM1fDNewuC7c5IcXF8dDhOcp1JZUTo+2tER0fpbOZfcxBywXJS2BolKEjxymydq5lxpk0FPEl75mFS8Ae7cCB37Yv8hnP4AwZS6U3EtsTntnuBvbSaYqTERrp9/I19g1ODcIln3ZLTIlo2VvwEASzsyuaOV24phJw9/dqMVg/H9SgxWJd/X9woPV/Vb1tIZZ4XFiJKV6h8dJw14LmuFfTAl0N+oYd8vaVnDmmXufY3lekqUr7Tb+GICSQHDmUhudiU2Y2uM5w4yzp54+n9+htfBIMBB3yacVJn9SID5v1ZlQiC6VixFN7LHrvMLU5oz21BRpZcvi2D0Yk3daxFXVT9OCUY3oy0cs7agJMo3EEY3KlEl6ChHNMzf8xfn0m4m/Pt0MxJAHWsojRL0QQvDxtxhfIwjSk+h3Rlh1MjecFacJCo2GFj6P5rkcJrJYyuWSXEmQE4vI4T91G8dK3nmtkGJrDVH4AkCtZedjB/zEoBq7ayFgoFtHF4PVks3A34FZCYHRCWFJj0LKVKsz6LDGoQWfB/yEXp/lZJLSug5ocByspMGdmjamUEdwr447d2JgJ8WMD3Qf8JLE3qz5BzVEvQW8LMMi7WHI5Lgfw+WjU4GknMZZxux2wDVWZ6rRbv6KUfLwgpO5heJlYg8+HC8vDG95OHFOA8mpNlLB0lVKUOI4lKpAobIEwEbEXO/IG+88di11B00SaQpzdSeqDnBdMtmFnx1nZHrVrGwWTs2UtzrwR+qlMVZ138c9R05Ob8i6RktHiysNeyGH5EnxS/fiSVOSiSICqZNOLYbooqgo5KjqhQsAJ3OyVsp/sBxt7xREZ1WdbRXZRin4Ir9rj8WilnYSHTOv/SG8Jhr1Tn5bO+SkouDKTe+UTeDgDt238AXJGbSWrhsfZ5W2HdGbiPqPkQevz/cwIdRT7clp0OFaMo1DK1POyVqs0CpEuig7Xhef7LgpNAtiJhSpuHWkhyvNNzILtkymGHumPMU6SN+7owY3J1uAEohl6IsOfjwmzh6J3u0Npwm+jgePzmWKR5fCfIs6m+LtOlp4ITmxGHTo1xzs4y15funpUZXOxtM2Av/jUnd1ZonOE4RWvBvZS2ruEYX9KdGivfRM7x4UjwS4eNPW2M6XDRyuQD9b+Szlk69eh5if2N3F+pfl8IB6XHKGn90QwA93Ahegn2OHHVu56ylZCn1NNI/aN3BTa2JIwE2N0uA/JdK74bNfiDs3fTvVKtOQPBooFVSeQyahOOEMt74SWQEeoz5Pu3Fz3MXdSYX5NAQgWyex+w1k0ZLJoacs3/obhCL6nwZXxJJ5GIe4LJJ+q2Hg8AwT89PKwArj7Ty1DkMXJGpg7/BL4v1DtI7r2Kbo7avbPdMPJx/GvrOytyw0UtPhb1Jaz/dT7Ag2m9/2TUFHOaZ1zU2ONqFLbmxVjwayV9FJYyVIMJLoDV+BeSZEZ0r3S4FLiAr2E58cUTeyFDwKb97zfZCmCxeeOtxSf3Qba81glvX3WpqiSkYFgt2EBLN7epfM8E6aoDyrYz1FqNxZpEbep2b9IQpPFEKmufMqaeM3T+tDHO2z+KTlUA2egHpZ6pYE/IPy46Oxg8NkvyZHrkSFDCGkuoGYNWwrWffZMqy1GisX5eL8ENyuiQHFH4SjgUc8AAA=)

## Pipeline 流

该表列出了多输入/输出推理用例中使用的插件：| 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-multi-input-output-object-detection__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-multi-input-output-object-detection__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-multi-input-output-object-detection__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-multi-input-output-object-detection__ol_kgt_hnq_nbc"><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，会执行此操作。<ol class="ol" type="a" id="gst-ai-multi-input-output-object-detection__ol_drd_jnq_nbc"><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>                                </ol><br><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 yolov5.tflite 模型进行目标检测。<br><ol class="ol" id="gst-ai-multi-input-output-object-detection__ol_l2x_zjq_nbc"><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) | 将接收端上接收到的推理张量转换为视频格式，由多媒体插件进行后续处理。 |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtivcomposer.html) | <ol class="ol" id="gst-ai-multi-input-output-object-detection__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="gst-ai-multi-input-output-object-detection__ol_kjr_fvr_lbc"><br>                                    <li class="li">Waylandsink 将其接收端上接收的视频流提交给 Wayland 合成器。</li><br><br>                                    <li class="li">在本地显示器上渲染视频流。</li><br><br>                                </ol> |
| Filesink | 获取其接收端上接收的视频流，并且将其另存为 H.264 编码的 MP4 文件。 |
| [qtirtspbin](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtirtspbin.html) | <ol class="ol" id="gst-ai-multi-input-output-object-detection__ul_skp_cds_nbc"><br>                                    <li class="li">用作网络接收器。</li><br><br>                                    <li class="li">将 UDP 数据包传输到网络。</li><br><br>                                </ol> |

从主机拉取文件：

    scp root@<IP address of target device>:/opt/<destination directory>Copy to clipboard

## 示例模型和标签文件

Table : gst-ai-multi-input-output-object-detection 的示例模型和标签文件

| Runtime | 模型文件 | 标签文件 |
| :--- | :--- | :--- |
| LiteRT | <var class="keyword varname">yolov5.tflite</var> | <var class="keyword varname">yolov5.labels</var> |

## 已知问题

- 当使用六个输入流运行应用程序时，会观察到 fps 下降。
- 对于 QCS8275，启动应用程序几分钟后就会观察到画面冻结。

**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

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