# 分类

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

**gst-ai-classification** 应用程序能够识别图像中的主体。这些用例使用 Qualcomm Neural Processing SDK、LiteRT 或 Qualcomm AI Engine Direct 模型。

该图显示了一个 pipeline，该 pipeline 从摄像头、文件源或实时流协议 (RTSP) 接收视频流，执行预处理，在 AI 硬件上运行推理，并将结果显示在屏幕上。

有关用于分类的插件的信息，请参阅 [Pipeline 流](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-classification.html#gst-ai-classification__section_j5t_2jq_nbc)。

Figure : gst-ai-classification pipeline
            
            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5axmgpPMhSmAgiiZOrW9znhc81AXVjEH1kDd3d10CQV/2MOo9CAtuwCCcHsm+7PSgjDIGwoxFFIV28EHe2RpPdWOrdjVcdYx7y5/jQvefYh3n2Ghr0iSm7I9Zy8E5eCcvBOXgnLwTl2CMqja7HxElNKvKAVsyo7oPvPsQ7z7EQpFO32fx3srEO8+/h3n2Id59iHkFX92giGlCBUT1ke4cW8zxi0CIYrIzx61u40rLnh/js8Ce3PjMO7hr7Wfr6tshBEJbyz58ppbE4AZMgbV6Q9ulx4ouisAbvy5iM1pfjegM27R2F2uGQrBS2xe9Jv4h2Me/NkW8T6peNVsh1JOojGq46xquCUtpqx6rjrGq46xj2EsEeRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGPkbMCPidiXL+Q9PIX8n6fGYjD3/mw4kREl1hajpj5qYEGpxQHKjd59iHemQTn8h5dn/Yh3ZqcUByJKaVcdPmpbE88AfefYh3nw4jj4iSmlXHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVdrR3UiEqL0wKkQlRpkJatTAg8OHR+rYVhHdfZoVjzy4k558uEaHuj5HVR4bg/cAhhCe25TlHhcvD486kCG1Z+75Xaey0O4FghvVDcV78Xr3bxOsXp6EpUNsXvyjTITHbfm0o9qrU+1cdPfENy/kO8+xDpj5n/W6x7z7EO8+t15HkSU0q46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquAvtD82xTnUnhz5brCU51J4c+W6wlOdSeHPlurLEM9iyO4aAc3L64hTa+/RMQoi34G4wCb8kfqDgQtd+MffR2IcQZn19PoK7eVSRctQyR89f66tyTD91ufTQJTnUnhz5brCU51J4c+W6wlOdSeHPlusJTnUnhzci7eiHefW5/zMSgjyJKaUZ1QEQpHVXHWNVx0+Sg7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvQbxElNKuOsarjrGq42dzW+sjoZijqpPDBy2n+ZzjqdVGEiMYXUwKsbG6CP0uRsIprdBH6XI2ETfD3Y1GPwPcO8+xDvPhzYikPUMaVcdY1XBJBRDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xCm8mFj0Acs5M5xN4c+W6wlOcTR4iSmlXHWNVx1jVcdY1XHWNVx098Q3L+Q7z7EOmPmf9brHvPsQ7z63XkeRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq429QkOJ/Id59iFJqWxPPAH3n2Id58OI4+IkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcEVXCRquOsarjcBmw+bHUQ7z7EO82PhzSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xqrqurHVuxquOsY95c/xoXvPsQ7z7DQ16RJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46e+Ibl/Id59iHTHzP+t1j3n2Id59bryPIkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcbeoSHE/kO8+xCk1LYnngD7z7EO8+HEcfESU0q46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquCKrhI1XHWNVxuAzYfNjqId59iHebHw5pVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1V1XVjq3Y1XHWMe8uf40L3n2Id59hoa9IkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1Erho7HoA6GYpzqTw58t1hHoVfW2IEOxquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46wP0n5/Id59iHdnXuf40L3n2Id59hoa9IkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1Gge4d59iHTKPq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarf9+lhpx6iSdRGNVx1jVcEpbTVj1XHWNVx1jHsJYI8iSmlXHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVxuCKRclrPhF8bE/kO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvNLyG1Go4rjEvgZx0nUa5unsvBj8yuWybfdMVX1dj5LTL3h5PzBNttOYQGId59iHdnXuf40L3n2Id59hoa9IkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1GgQXT5+17RoEEeRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrAdA6SWGwT5wAkogX1xWAaEr+yuUYLvE+3FEjxYyeQlM5g57WJ04E77HkIy4PdjVcdY1GdUBEKR1Vx1jVcdPkoO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EKUJrlKJ1jUaBBHkSU0q46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xtGAT3/Ol15q0HyR8+IbYHHoWGuEjVcdY1XG4DNh82Ooh3n2Id5sfCJSXI2D817NkPKOhmKc6k8OfLdYSnOpPDny3WEpzqFzzEGqm+B7aJ0h302YcQMw4gZhxAzDiBmHEDMOHjW8WVmOXOeGVvxt6XKNNY9AHQzFOdSeHPlusJTnUaCvRuwHOpfO4oLwOTw58t1hKc6k8OfLdYSnOpPDnSo223OTq5/lNYe7GKg/rWOaqhnuIEbeE1oEbeE1oEbeE1oEbeE1oEbeE1oEbeE1oEbeE1oEbeE1oEbaFM7cgbCjEUgbCjEUgbCjEUgbCjEUgbCjEUgbCjEUgbCjEUgbY5irF3890cfRhRIcT+Q7z7EKTUtieeAPvPsQ7z4cR0rForgHMgsiM4srZuowcr9q3VMTLWfnLwTl4Jy8E5eCaJbEc6iHwsIf0apEJUaZA8KsOkmpMDVO2R5X7D9p/qCRfqrjbzxoSh3+3EvAqRCVGmQPLRtE7Bix7z7DROr3a4To0TfLdYSnOpPDny3WEpzqTw58t1hKc6hz8PadFSmzPcSo6TxHDny3WEpzqTw58t1hKc6i15u9huxigG+MibHoA6GYpzqTw58t1hKc6k8OfLdYSnOpPDny3WEjD3C3mzSJKXWGALA2ah7sarjrGPeXP8aF7z7EO8+w0Ne1aM9KY+v2f9FnD/21s+eAmZ2HmrMJ+MlFya3oEFMgqN3pmMP1I8WBvElxswUEeRJTQ9jlaCweqkhlbw92NVx1ghJl8q9rlIkppVx1jVXYi7C+XQSZ5HkSTsMemTrohKjTITHbfm0o9sW70ofpfShHSpNVIsfBX182RpaVkIkVY3mSeND42MlV8Ws/OXgnLwTl4Jy8E5eCcu/phdSkvZYT4huX8h3n2IdMfM/63WPefYh3n1uvJY+9DnZwLy4yN+wfCNumUBXiC0+yMKyNPw9gmO+v0njrxLIeK51Ij3j5jv/4wBUpnLWCZxW8IGWaHbQ+F/YYvTQ3xz+Q7z37RSVdJjiwZPnyj+bHMBbGBGa7MaoRjBl0KDDDsTKNrmpYh01p65t+o3f5ZLcxfgpxsv+hWP5ShHj86RDw0Sdhrp5mvhOkmE+Z0ydQQPL8c/ZYg+MdRc1K7Qo7sTkyAv3LOJhCSJEVLQnwX/pl7eqLDtZte9QQ67IWUIAGWf8rrOSdjE2FPoRi6tKuJ/Id5sl4vE6SmlXHWNVx1jUaDfvKrVJD1KLMPVfDWDw3mt0iiR3IQpKPlePCFu6vnTt4Pn6FJ6AUc57WMmssTfirXG6NWXZqg0iLFiejYGH+jiKqKlrd4BG+beJvxonWHuxquieYNRx2exuDEwXCkQ3L+r/cIwIinlrOHNQisOlOPdDMiRdGEAIlvlWTz8IzqcUByJKaVcdPmpbE88AfefYh3nw4jpqN4Oa7xiQc7PsBVcOORG7IWvJoZe2RS+I+mHaFzcCqYFhUVppwLnIF5JuDUtJCOhqmJLyqMAr6fCshKd5BB7yUuX/w0Cpfa9CDzKkEgW8BKPeObMK78ZzEUyzx/izn+FHq66Y8rT1T8vSRzqH9qadI62NeCCa9Q3Db9pEFtaAY8DmebI0RKISHXOOxAbhI6AKPwp02PFroa6zN5tLMrdNPXSMpQUQVOHmm83RaBeGAhqXFA0P4tk7xnJTahypWbkg3yizsrY5pEzEof4DjiRsSJoV24YNyVPJHhr8HlsCWhF3qKoKOXJsf9GK2NFx7et3qAAFTLIyfjP00hicK/YE586wrzVvunTrKBerUYv27L9KaK0Xsadro2hPZKX7GT1bLVXgWBS+8crX4kBMev40WxchvGoRI5Ea07Nocm1xYb8VuzjU7UdK66hgSmJHko6wl1qO+8Syd+EtVX76hrGq46fQmnrhIxQPK2KPpE5/iNnTx6w1dRFCyk8OZ7JdN3EnN/z9XVKI2LjbCHwy1M5fYfRvhX7rCl3tYysMdY57Af8Arcv9nQEnlSc4xFCq3vt4hShNalgYyurW/d7tugbXx5qDRMC3y5LieeYpShJmQglrPux/7sy8wXYcfy3oeAY4zCoW91S1HvLFGrjrGquzYijl/y2w2INYc5zfhBMpA+9kEbtJ916b4CCHdvqw4tE5DyTrpn0HbguSgBrVQ04BIjHITj+ThRdTAfhAQR3Gf5jqJqrBuKG7zZMADZ0i+IW5YXuJ5zZLieIGKz5FSLQ+Tm+88Xp5ol9fk2t0a1YaEH4UFgNK2FzlOAfT7YpdgilVVDirALNwdOE3lpt15jCdd3nHYBLxPzzFARva4XBr0BGRLiFLYDWgcigEcjG4EQRAPhwRUU+BZKXhuIVpvjgrg8VltLLijw5SIkppVZseSMCTl4aclWQKbXxkiccpXkE0CN4acJ7gDh+jC3nu/KKmAKwmcPHyXD0WeT1YrwjBEjULnqhzg9fZGQUoLlx4HYR3ti+E6QMsykZTqGA/RY3hbRNACDhVMAgiinV9zplilWLZj0haZroIUU1FcipRBZ1DCUEZ5dULw2LUdcbATaC+55pEqs/O9NycuvwNXlyLKQ+a1dPk2/DyBcgAR6QSjdYRON5dILOZx5ndaAmMHX0GYggAbdkKj2p8o2YXzAP52Iv9E90417J3IpUoPXymzxAxFU36flsQQVVVcAsvjgrdn/7S0RUBJs05wCBV+N5q+zTG/YTn5aQ2VKDcT5zo+2GXAPgoOSuKAlJFMEUbZb5P2M/QwPBuFCBHdiGqbQrSEdStVSEatPYrqreQzhWKQjYJwPDZ6pkGHQ92Iix/8n+LCuO70bFp1QFuHhmFAGx6gOZq6cBRNx9+ogS8RUiT1culcF2ALreCN/9/H+FO0VPBrsusnmDa2hp4GGluxNjiMlqsC67W2oOdNM+gwwZwysgykM9T18XURf2l+GYYVkM+1pCkW6MZ6hpHCI1CBrc9nuHhopQttvopgwHc5w+cDSmgA08J+buRyix6y4DYvJFM7Pfdit4VW7ZC/XAvYRptfXFyelAaVeTKj2JrUVoXLStUeqHwDnwE0t3peW1EnWX0LTErg2njE4Ouf/LDyGA5E3+iMNLK2MUxdj0UEPs1HzW3N1yv74RKmOAhKGU3LHHkNQoCkSU0q46xquCW3eFAkBiIRz2stIO82TQoaG6Hz7F1EtVx1jHxmAxgbNiSjl2T3HYh3mx9vMkJ/fkO8+te0kMZZj28wtND/fxlp+whiqdRmagkn+AG9Cn9Zyh0BS78pLeQjZsdDhywMmpUUUQM6lQFMUpgnHi3G1Wk4YBzRkohUfARRH4Vk7w4U+a39dQkg5ngVg/J72iDOPp5LjXjLbf0APAGH24BhpunvGTZmv05Q4dOhK4nzdhapGecEYeFfKtH4nAKXGayb2B8uQKih//VhPZMZPNNuRtEwhgJ4aAt7eYiJWvlNYcFEK/slyxKwXpm9547CbcGs0YjcUoYEO499HC7dxO6euC3di2GClnYN3Hd79Krxbv+fvtss/DmZ8WbRal5rMghJ1hemsZH3ZhS5zgDk/ERWh+AfABX//KQhnnXskIBof/Gu+YEZ/RsY2SgiRqcQ6DXAHQ22Ep9AtKWJVyURrBF0bm+XOpf/fyDEPe2hQYndUbGrstKnnPb6OuKOSNFITOB4EbdVUvP3eZetWWu4XWve9XHVcIQY2u/HUDP9qBw9zm6TRXmoeHBFrjEJgFbIAU/GENNSfg5deuNpB4mPGXoQhOMXNS8FIlnqxQuCXs5ZZJ/w4/BgdCsr6zXlhdsrhx3MgGxw+tA3E0AM3j6bgJhatNqNNYGiqlaMm2B50sp9RehIfHfuzGce9RQNQ6nHkbxsf9QqUDqvxASkobmhefdmQQvVLn5CQ8bMo16cWnhVUfVx1jVcdY1XBLbvCgSAxDvPsQ7z63dGPTFlWHuxquOsarglwkY8fHI18tkRJTSrjb+Q8NAdjSrjrBFRi4JCrkEb7zzCj5WpcTeUb7sdDanBjaqmCtX+LEDKn6QmBi4F6nSUzO2qcIuXKCvt6tKk/RWeS0Fcxzpi0D/pwxFHD5oS3yyeXgHw9YJb1NCpSqP0B+UFfy42u88Z+vBBwIiV/Dx8ppJ8N4fVBBps6oCIUjytsjMVzU4TWaCZ5Vuxv28MTVSsknicpSBm+W6wlOdSeHPlusJTnUnhz5brCU5NGvAPoT6paLedZTsegDoZinOpPDny3WEpzqTw58t1UXh/LY0J7FCLOsJTnUnhz5brCU51J4c+W6wlOdRHZRePIL9DDNweSdS5RprHoA6GYpzqTw58t1hKc6k72+z+M645I35DvPrdyfgge5QUVH8h3o7GlV2tG0EJ1k+DBtXmFZhj9SX0Q+amBPL2ruJY+J1n2htOs+z4nHTQoh3mxTMPZgouCrVH67TDHuzlxgR5ElNKM0F92NVyZOsIprdBH6XI2EUyZ7uS2mQmO2/NpR7Yt4vfSfYh3n2Id59iHefbGJTVfkl4FSISo0yEx235qP13M2AxDvPrdyfgge4enktaUe2LeL35RnM0Juf8m54b+VV7Thp4rJZAm3I/95U8otMmvYL7KUs+CiQHWrLx6H3EgaTJy7bs/jKaWkTLCvgPljCdeAvIWjkiOh6wSIiP9+UX1/Q7UqU+KjtSoxbueRJOsXprilZJ9iHdnXuf40NekSU0q5A9IcLgoI8iSmlXHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNWMJyRvyHefW7k+66Yty3U1SjTWPQB0MxTnUnhz5brCU51J4c+WKlETM/IofpOdOsi3u1eTRsE/tipRMsCk9Hf2L1jCRpG6wlLDCnEanNxYHCtYvClJJA4Q2TVlXQa8LlR9XAX2uZqSRHLdYSnOpPDny3WEpzqTw58t1hKc6k8OfLdYSnKkQCIlRElNDx8ceId59iHek5JLrDekFEO8+xDuzlxgR5ElNKuOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjcEiIe7Gq43BFJA/zYRTW6CP0uRsIprYIcqbi7XLLdtee2af5jqJqrBtmn+ZzqLyJ2L6q46xquOsarjrGq46xquOsarjrA/SdJTSrjrGquzYikPUgoh3n2Id2cuMCPIkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcbgkRD3Y1XG4IpElNKuOsarjrGq46xqyq5otxknJKr0tZ+cZ1t/D3Y1XHWNVx1jVcdY1XHWNVwRVbeIkppVx1gh8z/rdeR5ElNKuNv5ERJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xqNA+kauOsajQII8iSmlXHWNVx1jVcdY1XHWNVx1jr7uOsarjrGq46xquOsarjrGq46wP0nSU0q46xqrs2IpD1IKId59iHdnLjAjyJKaVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XG4JEQ92NVxuCKRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquCKrbxElNKuOsEPmf9bryPIkppVxt/IiJKaVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNRoH0jVx1jUaBBHkSU0q46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsY8fGYEeRJTSrglLaasewlgjyJKaUZmv7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7zZMQNz7EO82S8aVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jHj4zAjyJKaVcEpbTVj2EsEeRJTSjM1/Yh3n2Id59iHefYh3n2Id59iHefYh3n2Id59iHefYh3n2Id59iHefYh3n2Id59iHebJiBufYh3myXjSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsY8fGYEeRJTSrglLaasewlgjyJKaUZmv7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7zZMQNrPhz7zklCWXBETCeqmpA2wR28TQ3w3lKcR0vGlXHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdYx4+MwI8iSmlXBKW01Y9hLBHkSU0ozNf2Id59iHefYh3n2Id59iHefYh3n2Id59iHefYh3n2Id59iHefYh3n2Id59iHefYh3myYgbYKY7uWygj0gIShju+9Z4BUraR5RE+nxmBHkSU0q46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsD9J0lNKuOsaq7NiKQ9SCiHefYh3Zy4wI8iSmlXHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVxuCREPer/HfW7k/h7sarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xqrqup9q46xquOnzUtieeI4+IkppVwSQUQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPrdzNgMXKppRoEEeRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xjx8ZgR5ElNKuCUtpqx7CWCPIkppRma/sQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvPsQ7z7EO8+xDvNkxA3PsQ7zZLxpVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdYxVJ4kCB+lEmJn5lPmvlo5I6enlkfN5zGXjUZgR5ElLw+Z/1uvI8iSmlXG38iIkppVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1XHWNVx1jVcdY1GgfSNXHWNRoEEeRJTSrjrGq46xquOsarjrGq46xquOsarjrGq46xquOsarjrGIPBWLw+Mb3j/24f2E+wmDe1EzSBRRFNuF8BQoMI6YtcCHZG9GuWrwPdyqaVcdYx7y5/jQ16RJTSrjp8k70pcjYLjESK65y4c+W6wlOdSeHPlusJTnUnhz5brCQxwBrRyIItLyI87oUYikDYUYikDYUYikDYC16Bo8EYRwyg7wmtAjbwmtAjbwmtAjbwms8ZnGSXg1pvqDhSqhnuIEbeE1oEbeE1oEbeCJFgFVm2fHJG/Id59buT+HuxquOsarjrGq46xquOsarjrGq46xquOsarjrGq46xquOsaq4t9ilc0B5dBo+gHUclGdON981IY7dRikZgR5ElNKuCUtpqx7CWCPIkppRmbFdcIjkTanhOBC3UiEqNMhMdt+bSj2MAgXeJ7F1E/2lMpSISo0yCABm3CQM9L8kvAqRCVGmQlqkCeVS5pY6ff3tKird5uNWY9FHihk+fYh3XMiGG/2eGZ7iBG3hNaBG3hNaBG3hNaBG3hNaBG3hNaBDRT2laBG3hNaBG3hNaBG3giMPY8CNvCa0CNvCa0CNvCa0CNvCa0CNvCa0CNvCa0CNvCa0CNuqgBlPlVE3oORPg2tOOQ92NVx1jUZ1QEQpJQd59iHefDiOtvidpPXWqkM2Qa+ps8nu7DEWhe01arjrGq46xqNAgY1qEkpIHBRca59cMfOp2yLSf194+uBAF4i7eqFE7kfMhpDdQ86aDlfaXyajRkFrD7z7EO8+xCkdVXVcAfefYh3n+fbyyaifHI17Vx1jHxrx/YeFny3WEpzqTw58t1hKc6k8OfLdYSnOpO/G0bffgHtroTdzTVKNNY9AHQzFOdSeHOVOKKwD8hoF3yOinmFWDbNP8x1E1Vg2zT/MdRNVYNs0/zHUTVWDbNP8mWXJJZkoPdrL78YNKoKAiHefYh3nw5sRSHqQUQ7z7EO7OXH7Yz87VJnuvuTa0xR9nNXb5vwPcPTEXg1+NKubDsYthcBR3NXU3aKCUdDPI1SytRTrv7UIYmD5e3fiNk+L1YvR/iUogUjzNuROpldikYVsBdPb+Emas0LH3fGyTNUEJQUs5tu2mA44sx9EnZONvHziz76NDdFeFpsGDiP7HU53Sdn6UBAisfBBX5TRP/JlO9C6elt2vRjnwuyJ6wNcfjc0m1DnNYfUPVh0zLVIRXdeSK53M4QlYOK8A6br4ou8fDwk4aaKycNROXURUA3Bnzj5soKQiS62P1209F4/N9yATkYMm9hfmS5fyHefDrRtFNb35y8E5eCcvBOXgnLwTl38y8aHxpmYgGoQa5I8uQWFYuBPUGeDh4VAnLa2inh55dvuFIob6PSYkb22Qh6C/DTqKbzbeHUk8641eCcvBOXgnLwTl4Jy8E5eCcu37IC/kOl9J0lNKuOsaq7NiKQ9SCiHefYh3Zy2+Q+Q5sGvX0AIWrwp+qRzffpOPZuflAdRrH+cOw0Yi7MpmM2DTZgjF1/EpvNN4Lv2Typ59vuCKdUqwAzmHMTzEV60CJUKx4ZGwetRUsGSis/7FM37HKaqnB8akMPjdJ8A4oBXFUE9B5HuwFJncXlbqFlqJV8+qlLQl/E6MPKcxGpMUXEqKxAKIvX4ZhEa8Sd/N+gTso3f4S/423jjxIco+lcVFdZCf2kI/MrsTGWUxWXzrGP5gu9dcl4aOT5K+NmdZKTofz2436Qm9NfZUJ3bG195q3MHBUcbLx3dkkobWbhHsAfhwf1kY6ND2ZdbZwM9VABZnb29mVKXr1bQiVrK+zuDTliR7Iu5MxFmzOGCth7CFuonW3N9aDWq+IL2wP/4m8YCscEYxG8di6EfD1a7IzLxshNOqsvHjKOpPcryCg1EsnXFvGROSLqSmlXG4JxRE6SmlXHWNVx1jUaBBF8ZbhgYYPlkzebyClfi2teA0SjYSZ3DN9fZWz5vPmXl6KyX77HsxvxizRjtYrWRQbblnSqgJBGbPIKRuVhmHdI4QhNavUIpElNKuOsarjrGq43BBWZZIuqXLM64nqZxstjuUCcAxg+5RT9OCPmf9iHefYh3Z17n+NDXpElNKuOnyTkaNJnmtehFNhbnbSXmcXCR1gnULQe8u2ARcyEJMtEfSmgLzm65h/mB5O3Vp7ik1S+pZg1r492C6u4nXj25DrBzHAxuO6ja1cPZGTLFUkIRGVQSt/Gh0XEW1cRRkq321dpcfPCWXy4IH5nUYYoqfFgsUz6p+MKlvGeDJ2c02PMEkwQ4LTDZ9LJOxF2On9QERDviM++juLPYNO1EeS0xlDF2BD3x4mdDIsiQ1LgJUAnEznR1fPLUNydNUPZgoI8dXbwX6ZiHEO8+xDvPsNE6w3re/ZGUOM9cCzf9Ms5iHRkTRZGoa3VIxpyNABzbZkAZzwnBf6XV1OqwgKW01Y8fGYEeRJTSrjrGq46xj3qAp7Ulooz45gJEGIElR6GWAsEZfVRg/js0J/lA3vCk/RFrbxElNKuOsEPmf9bryPIkppVxt/Iqov050ej32VOWMs/Qvxxd2JT7WyOfu+EgGjGCVONDigORJU4sdQDutzoC1EHqSh7L2eIXpcO/gT5cZx7vUtDwovA//ANu/VZi2Q9M6JQ9eYPTbUw23+uD8TJtjDju/LX3DuzxQG4UBpQSF0sNaK6aW7mYoqq3DmC7n0RVeDTw+3UQ+hvQ1jVcdPokQIkhadJO9UTx80/12rvZkhMzvgS0cy8uf7E2vrPS8ZJ7eTjSYr1F+gv9emIS0Ss5VRTc7R2wgPtQ+afhSfFphG1icdC/xcolxi7F/wc9aKA0yt//KAV3O9xibPvgklxT9REPNkHF++UorOg30Q98KXlO2kZ9OCTjirG0JVMytr6lxFY1lWFIQpAskeiK+eQspKmJXK4QWl4qtapppeYmiGLmZ+NQWukvr60Q1jP258b2IqqrEqNKwOlLxkovEs1oegdJ1u3V4D30tt9u/QXfTfbw5C+OCZV4IXbXMOwkRph3iQ4MNHufNiXF0zXSGJqmXZG0aMJVTCZvfj2GNqK+PYKXkQkWVGB/HHHrcRkZbeKhmLuGqzjdcgoyHRcn8PdjVcdYIfM/63XkeRJTSrjb+PkXKn1cos7B4O9wpi5aE/P5DvPsQ7z7DROr7VlHiEvcRbtKqVfjKlDPszwNqfIVMB1TeGkFcWwIvjkPV/TRqybnWNVx1jHxx4aCE+JgjyJKaVcdPouSu6jJESU0qs0onysmETaH/8E581JPoz9sabINtkccPH6zXy9eLQHCL1qj4eF4HJsqw9/wgWoUC9N37YcDshb0AhP7g77g6iD4BmqO5U96VbhonrDfnI2QKmxMxxyGxzIbuGfteGhpCDYlnbU+QTzx54qk5AY9ud31utzwgJ3CVOEBddnWc6F/QvXYw7YCy3blfKrvyOXsl1kekQGSEHp4umFdRK+VznJFZpNdrsrfgycYt1xgvpOPY1csFDEMGlyNKUWswbmssgZznndmVwatSZeFGCw9cPKenEHS93Iz/xzAVjei/6DH8m2gRtZi8pZDjdM8FX5g3L3HPZTAfGxX1Qq5JrHgdmdiLux8OfcvR8p0o78JEM47s8uAEG210NksY4cUPzMfRTEO3hfYOG4cyej0YY8WNjGwh6hkHzNGquh80AlZlzf4ddX5K0B8phuoO1xYaaCux35jQAn0EyaSmRhkZtfPbSxUtm0KlfERAIZYZC+CNCIwyFXpgsnKkjVDw61FUZ21Ay8ZFPv87WuL/1OZ7GQdyfw92NVx1gh8z/rdeR5ElNKuNv5AVLWxM9ENQgtGVuvj/NNUo01j0AdDMU51J4c+W6wlOdQ8Vw5OostG68++iGUUgah+omqqdDpu2NvCazzooGyYhKyG6p0MxTnUnhz5brCU51J4c+W6wlOdRZSed/3W+6pwZ7EoTW4c+W6wlOdSeHPlusJTnUnhzmS50C+XrocT+Q7zZLO41PJTIzNmjtyKA+TFFBFyEy/1RIic9jXGWjAQLSXSLVyY74pDabazwlUwCNdiMSE414KpO0VioL9iF67j9XI6nzP+tz/lHrT2QSOJa98Sl/iSuOLzSso+lEV1MaaVoN8Qmt2NVx1jUZ1QEQpJQd59iHefDiOPiJKaab+7QR+lyNhFNboFQKspZ8apoI/TMNzyxvWGQd6G14Jy8E5eCcvBOXgnLwTjOg/GRORJTSrjrGq46wRP2IxquOsETv6fprhgR5ElNKuOsETpJ2GtrgoxH3B1LJyabX7PRT0Ar11tMG190yx9oHOvX/5P32Sc/yHef6Ba7z7EO8+xN1H1cdYH6TpKaVcdY1V2bEUh6kFEO8+xDuzlxgR5ElNKuOsarjrGq46xquOs+z4iS1SEY1tI1XHWNVx1jVcdY1XHWNVx9KJ9KJ9KJ9KJ1gifsRjVcdYInSF+mYKCPKjd5/n1ufQmtYIqNxAJJb6sqj95x+PfDScFKbC5BZm9T9h3sZmmue3TPpGww6Sc5KCI+Ht11p+gpYZqvOf1PEv8Lpevkl1hvKrbxElNKu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)

## 前提条件

- 将模型和标签文件推送到设备以运行应用程序。相关说明，参见以下内容：
    - [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)
    - [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)

    该应用程序支持 Qualcomm Neural Processing SDK、Qualcomm AI Engine Direct 和 LiteRT 模型。
- 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。
- 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。
- 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

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。

## 运行应用程序

示例应用程序使用 /opt/config\_classification.json 文件读取输入参数。

要创建自己的 config JSON 文件，请使用 [config_classification.json](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-sample-apps/gst-ai-classification/config_classification.json?ref_type=heads) 作为参考。

要运行该应用程序，请使用以下格式的 config\_classification.json 文件：

    { 
      "file-path": "<path-to-input-video>",
      "ml-framework": "<snpe or tflite or qnn framework>",
      "model": "<path-to-model-file>",
      "labels": "<path-to-label-file>",
      "threshold": <post processsing threshold, integer value from 1 to 100>,
      "constants": "<model constants for LiteRT Model>",
      "runtime": "<dsp, gpu, cpu runtime>"
    }Copy to clipboard

    gst-ai-classification --config-file=/opt/config_classification.jsonCopy to clipboard

关于模型和标签文件，请参阅[示例模型和标签文件](https://docs.qualcomm.com/doc/80-70017-50SC/topic/gst-ai-classification.html#gst-ai-classification__section_hds_vxp_mdc)。

| 字段 | 值/描述 |
| --- | --- |
| **ml-framework** | **ml-framework** |
| `snpe` | 使用 Qualcomm Neural Processing SDK 模型。 |
| `tflite` | 使用 LiteRT 模型。 |
| `qnn` | 使用 Qualcomm AI Engine Direct 模型。 |
| **runtime** | **runtime** |
| `cpu` | 在 CPU 上运行。 |
| `gpu` | 在 GPU 上运行。 |
| `dsp` | 在数字信号处理器 (DSP) 上运行。 |
| **输入源** | **输入源** |
| `camera` | <ul class="ul" id="gst-ai-classification__ul_o4w_v4k_pdc"><br>                                    <li class="li">0 – 主摄像头</li><br><br>                                    <li class="li">1 – 辅助摄像头</li><br><br>                                </ul> |
| `file-path` | 视频文件的路径。 |
| `rtsp-ip-port` | RTSP 数据流的地址<br>                                            <br><u class="ph u"><var class="keyword varname">rtsp://&lt;ip&gt;:&lt;port&gt;/&lt;stream&gt;</var></u> 格式。 |

使用来自 RTSP 流、LiteRT 模型、DSP runtime、自定义常量和自定义阈值的输入运行应用程序：

    {
    "file-path": "/opt/video.mp4", 
    "ml-framework": "tflite",
    "model": "/opt/inception_v3_quantized.tflite", 
    "labels": "/opt/classification.labels", 
    "threshold": 40,
    "runtime": "dsp",
    "constants": "Mobilenet,q-offsets=<95.0>,q-scales=<0.18740029633045197>;"
    }Copy to clipboard

    gst-ai-classification --config-file=/opt/config_classification.jsonCopy to clipboard

请在 SSH shell 中运行以下命令，以便显示可用的帮助选项：

    gst-ai-classification -hCopy to clipboard

如需停止用例，可按下 CTRL + C。

## 预期输出

分类对象显示在本地显示器上。

Figure : gst-ai-classification 应用程序的预期输出
                
                ![](data:image/png;base64,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)

## Pipeline 流

该表列出了对象分类 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-classification__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-classification__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-classification__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-classification__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，会完成此预处理。<ol class="ol" type="a" id="gst-ai-classification__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。 |
| 推理插件：<ul class="ul" id="gst-ai-classification__ul_k3l_35k_pdc"><br>                                    <li class="li"><a href="https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlsnpe.html">qtimlsnpe</a></li><br><br>                                    <li class="li"><a href="https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimltflite.html">qtimltflite</a></li><br><br>                                    <li class="li"><a href="https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlqnn.html">qtimlqnn</a></li><br><br>                                </ul> | <ol class="ol" id="gst-ai-classification__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> |
| [qtimlvclassification](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtimlvclassification.html) | 处理来自任何分类模型的推理结果。<ol class="ol" id="gst-ai-classification__ol_ol3_dky_kbc"><br>                                    <li class="li">将阈值应用于所选结果数。关于量化模型，添加 Softmax 和常数（q-offsets 和 q-scales）。</li><br><br>                                    <li class="li">加载 MobileNet 后处理模块。 </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">将这些处理后的结果发送到 qtivcomposer 的接收端。</li><br><br>                                </ol> |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70017-50SC/topic/qtivcomposer.html) | <ol class="ol" id="gst-ai-classification__ol_dmb_2vr_lbc"><br>                                    <li class="li">从其接收端获取内容然后组成帧。</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-classification__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

| Runtime | 模型文件 | 标签文件 |
| --- | --- | --- |
| Qualcomm Neural Processing SDK | <var class="keyword varname">inceptionv3.dlc</var> | <var class="keyword varname">classification.labels</var> |
| LiteRT | <var class="keyword varname">inception_v3_quantized.tflite</var> | <var class="keyword varname">classification.labels</var> |
| Qualcomm AI Engine Direct | <var class="keyword varname">inception_v3_quantized.bin</var> | <var class="keyword varname">classification.labels</var> |
|  |  |  |
|  |  |  |

## 已知问题

- 分类对象的文本叠加较小。
- 文件源观察到识别准确率下降。

**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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