# 目标检测与显示

Source: [https://docs.qualcomm.com/doc/80-70018-50SC/topic/camera-detection-display.html](https://docs.qualcomm.com/doc/80-70018-50SC/topic/camera-detection-display.html)

**gst-ai-object-detection.py** 应用程序可以检测摄像头流或文件流中的对象并显示结果或将输出保存到文件中。

Note: 此示例应用程序在 QCS8275 和 QCS9075 上不支持。

Figure : 目标检测和预览的pipeline
            
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ewZDfHrhy9gv2R8GyjlNPQtAdUs0GkX2uR+6a1dUSUtulVgNAqJbKna/HmCitWfz/fg+a4Rtswgo5uEbMVsh6E8xtE0SfLQVBB6hu+bXazkjXrUWQxXQ0z1aiNWgGgEoWgYveE34eYEWpMZ9ZnsLQJBPOMXDcN7YJEcJ42SGSTIAc2Z/I6148lzQCpUZOH27YZ3aviFWasAv19ynFct216cUysNq8ysQa0jFmuzzaAwIpOl5twVqUgSlHfF0RDh7jInVbML6UoqVTJisteuhoOrUaRAlUrW6D9Yczv1zUBLwFLfQZUu0oWIQ2cFy0SH66yeDEOwOlzoYFD0C796zA6FVxh3INMq8403Viu2Sa5GvP3TFgmVZtbmVQDWtbUa7MNI6C+07uNSCEN7lKi67xDNgXYYYSvSGUNKVoodDXMVaMcJwW4Qwa8ctsgM0YNyDKgnOw4pe3S5Z2/8mXm6mpRcxQRaclCyYE9rJ4hCB3LAtfRxKNer01xLebv2VAnVJtfmV4D2iQcqAYUUf/p3UaAkKOhulDMeWzt8teWsuM5kQbqUzSngrVKqWXvB6oajce263IUXx4yWFD2cWpme/lUO1VVw/E6r6Pa7yXQqrKDHkYDe1GtyIw29bh6E/krMX9XzAlPh2uuYhbwwRkOPeUBy8qtw677ijZQAWpBtNe/VW52lugWCF8N29VoRC4NValW2TokMPCVCcjffQ2JY+yu7PY7yydVBesK93tLFdOTBfXPeKjO9MbGCKdP79gAard26CITlKNGKSorwtbatm2oWBUKZIFooSvFfS9Ca+sHqhrt5QuQ1YYGkH7SZGD/ZetDbeaePBS1CtlqvPLOUsU+7bqHCat58AWlzYGidTWduvkaTFHYQvayGVdXLViWpwxilkZd3RNUNRoPuaJMU4YG2a9+6izHr34FKevFHXkAmY9+yw9lAF0xyvsiUjIA3XGq7GFdB8PYKwzpVJcdKDZFwYUi3o9kk/Mnxo9VXQxqxUwhu2upPf0RphqNSaeTO15hUBBp7acpaGty/xopS3N2T14isjFsGMXcgKEajJpRzAChrLXWiamgU6OeSqwwtEIWPSvqNwFnOdQUBhKi9yMBFSJ+fiFKUKdN7J9C0g4pNRi6Giar0Xh0dluVdBscimPwkw1YBPH1/46UHfMd4ddvI7JXdWMYcx7Ck4/G9BGImgkEKveUaWBtVAJihSmdWtoI8nFp917Aewi7PQbMSRTzRu1mAsrPrQMLKrKqpABaSxh0NWxUoz1w+VDrRxs4OKxVGa1UAnelhmVGLK+hOt0awKPFPkzbDpGuuhDzg+VQKkuygO6nn1YtARBfoLSmOlYbPz5+NPkHEz/9p497L+AD498ms0nZlyKPEYK+4GIV14t47kMVhABdsgbThF7LMLMajU4FH7DwHRjUPef9BtLV46BONwRw9L2pc5vTgMmY41iQA+M72OkUpE1R9pFXA8F7Aef0s+PvY8e3dbuun+6+wE+J8IaZYmHOpZTDLFb1XAdzPwjHsZgnQxdKV1Qy1TBZjcYEfSBjB//LnVn02k4jt9ZW52QrdbpGrP4kfBvvOSXVFDyX0fktUlla0mz64ZhED90MwIdcNapX6u8Z81wfd24M1YswdjHj5hRVdMoSTguh5lL2oopCo6TkdlXpqlctXf2KgwJhq2GmGo3PJtWC79OC95tueZZOSQBFXbmynj6kP0KK1oK8GcrplKQJ8eRddO8ywesAdUDVmfJlXR/3TgzHITYwk7/Qvx31FpWmQgInxCw/N2LeZC+EwI5t160dodDVMFWNxgMbc3RK2hSBGUlE0a/n1bVcebnG32FHK+YvKk1Ne9hIOU1MBW5HuqC1UeQcpdgnF0Gssb1t6LCgzOkWkufjQwL/so9LgzpsNXcFDMghNgqVcfdux1JvUNl2WcIFCQEVnwYJbIRAURbq/VSOIxi6Gqaq0aig1SdsvW65dN+q0nMyun9dI4G/otazAjXomGAs50BTeVgYEGmIiCsNrg2wPqp5aDKhbcHm54xcSJuPFbX/9KHveLVT8fmzvvdVW83dCMPzIoyp5Lp10m9IwcXlUkOEwIrPKCnFxAqn2KhvuWLTEMGpDKxGo1a8h65Pr1eurWtV32ZLbmPIHDAnUIPuDR7LgXdBgoUxIjsrokoz14bQUk25jLZakbCs0Qt58fEZCPksjSPU3BMB7g4MJsb9miEOG78pxSgua5AQWPGBcq9WFFcoxbWaUkNqUE5lYDUat+JdVH06Pbj1wZJCUC+hlCkS7d5kCNMiTRHxpYW8WFL0GoPC8gYtJMznz2I65fOlCT6EjE+fPn8G8yuMmnscqMwFI2QYyXStZhZhZh2GFoIa++U4sqVxIoiU54YOPeiGCqGCygK+s4otqSFDPqcysBqNXPFWGUWGh1xFzOlOc81/UCpiSVd37TFAA3Pm4IUcrtafn/+TUPGf1PwKp+beBv42w7oohAxIlfLw62AU8PoZCYlKrULIi/lyHNVqS6NESG0VC7vlIpu1ehzbPqy16MA/v5AvSKyFLH5MzKl8fEANpJr7G+ijxS9/k8C6DzPypRSrAa+fkZCo1QqUvGgvx1G3ZEujRCxKGRZ220hdDv07BbnWEOkUrdKOfTliL+TAp+7hdg1BrJr7GsDkxdasxwk4dtS2w34kAPRCGHXTNFrEhmdDWlHCtFrQykVe0MtxBB+PbgHiGpbWrIe9Qw+XgB8K79aRfQefVxmGiGhF9PvLEWYhfcT/TLdP3ZE1pJr7G8xniBAJJLTIPVNQEq8MMVQzwGccpCZMANiMY8NieaSZG5rd6b7cQlLE53UGg8j1TQnerTS2yKsCbiFV4LE0n0D73MGouRshtRdhjEBJkjuGKNH7Tj3Z5CI+zBdY7ELQy3HUkEm7EgcmZmiQAKXr5pGzLvrwyKs5ufiWBN+hWGyRY8NjTbA9EsduH6SauxzKru9VpOxqmsS62gI8VacN7RpyXPQAaRuw4yjSDOtqpb5AabFeyTEa8A0oOW8cOau+Y+zZFvHgQ7FFXkOs93jAGQtxtyHqCBnrxwi2biZGaSidhk6meghdKBiIxz+mpRUpTc6jSLAZYPpHSW408Cgb9BxGbh451UOiz3xkNh5OAj6MRqu5w2HXT/xD3wXIhuZOhB4LNRdS1RRI0RoaQMyuKDapBj+/EGErYRNnxqalhXLqlSRW1a0XeTnOzQ2EsP9E2HmXA5qpqMtBcJ4IqOA8sTR0yItSppuyA5+elPlyHMU74alQNvyr1Hqfidczgx+DT7zsg1VzXwOaLOmBk0dOhTTQCIRieQ8movUOXjPqibu/U8C182Ov574nz6cPY08TVs19Dp2hSWG2ZkG8HEc9A0V0mt5Fgl1KHfz4ufL5hZBq7tPgvjSgLBnarr6/fwS3lCyfFcaJxMgdTUg1d2K0w2hLxbMoxMtxlM4XddzQ+0cwS6nyST1xVHDauJ/lqdN1Ev4Tq+ZujAW3etp0q7ild7X+ePcIeylZ/sOHOpd+NL+yfu6eQKqaXaHU3IH9EaRRPmiv/QXsHXIc6fwYWF/dHijvIWEtJc1n5pcohJUwau58/qKaCupORbA0BBbTPb+Q/qgIoEwLv//FxhW11usAvJQy4r5E8I4kHx+fhIxP/+lDGseoucuhgD1EuhkTghqfTUuveiIFU6sCmFr6QAredrw29gPtPXNbSe/PMbXWOi+gYgj0Cz7qDvwFXW3MQUvJ8x/M54tqPX9URs09DmCeRfwOQbbdoHRyamS6g2m0IWj3EzgpswCkqWWPibLjUOvIVKwmcG69yK8WrUuftaiuZCNM6sx6Fyq6uzNx4K+WUkee1/OO7TXCTe5FGIuOnrnBp1mnzCv6/OywsJgoOWWT60iBdKFvt49UWYuKobzXWlRXsuFFb53O1Pa074q3MYLoVyp5KjJJ0l1tvJFLd2yk9yKMRQYYAt/8oWdHk3ZsxMtxFAu9MlTTivG9m8CPW0fqsoCXH2Hby9ZfLQoq2eCid6lTGd2+OOdH0snYoOpf8dQhs5N2LCh3Gm26pbsncvwQnwekaC2RMQzBIjcgBAtrR0zsdaRR2RSQePtIXY6jFTlaH7Ikrf3UolJr2AcKJtMYRvusddRtJiZQyROkYEZ8PLxzI6UXYSw+SgT8/Rpe1iGybgd5zwF0xeWkFMN5FvztdhE0OitUaOmVMiMAWohtE4TCOwKy6WBwt9myl+0ennRfhDFj72lLhPnrS17gP+4KYhfvalhK2RRiH6XYlqhU3DrSzbGjty16M77Et6Bs8wHvt08o98cE4I7ZjwPdq879O8m+CGPG/eZhEUhkNQ1ZaiWsq4allbEpxD5OsS1RqrhxRB6gaE1Z91WLAtnTj5HqYfDx7CrIXhhq2AseZKhTcmy9d8Yk/CKMKQWGXEM6YQhl3RlsU4h9nGJS1XnLCDqW0Ziyjl6LanFKtlGVyuhiA2LCnEZdIlEX6gUPMsUo1UpOtaXdWRN8A+EI9KLbRurCEb8WrRUDqlIojEFVrPMZdTkOAX8ByAt4wYOI438XJcWW5qKhq0eJdSF6LboYtWhFVSmqVW2qrlhnMsyH4z8W3QMQWt6mH/xfa4nyDzdK3jt9AS94kIuGqh5Ba+gBxKLVog2+3R1wnOL+BUgZCEt2eQ+XsyHWg/CCPkE9RwBA24H4reDuW503gmtRQ4uuPCmKoQsKw59zGcaLHmRh9CXziSCiFzwIilG0XaGnZUoBPfMOnLMu6tjZG3aMf6FfkDi1aOnkwhfBqyLYfwFSCPA5413Ngd+0ZqBf1PB/uFHgczNezaA7cM4q7zX9NoBa6xS+GhCnFhUKQKEpIV7qLq21GYDP+e7HOOqieqD98n7sSq0UXhBdV1w6FXKmRSgTGmYbuodEnGJQzpKWTePGMPXWHFfa1UPuPjHZyNxZpye1m32dwD8GCK1FQdmptcgClqB0YtVZHmHQ50z3/EJqPWkamF4BMzQAsPMJYJPzN0BZF29RJ5zapHQTZ9zsbhpQk3EW+Vj0WhzM9kaNXHtr1I6dy14Nk4XzPM/pyfAMJHGzjOuduojj7qYoZ0W3rVdEhFoUoYtOGyF7MepQhP6c6zg5gBbVlJ4I/3CjKphUVMZNdJI6uD3uzuBTgLr04Cy8JCFKi4PZ3piRbW+N2rFzuT+LNzWGZyCJm2Vc2cBbPo4iHj1h2nKeiAi1qJ5JOQ5UiiKM0pORcxT1OVmAG1AsoTpgA806tKY0eTzaYRyMJszR3cjKo2cTaq3AYTf5Jh0Y/LsBrLWOH9XMyKI7CxJvSJKitDhok96cVwJgI/TaW6NKDL0ROJ2V9kZIWrlDqnf6e1VT9S0fsvAQH5OZOLUoem3MFzkixAPcHcOE4W+vXjGG3S56pFx4RT1pjBsHZhBsL1UjeSSg5w/UDsd17KgLlZHFdRY0PjG/5AMQpaFNenNeCYCNELm3WrsD9iwRx5c0VtrbIQnlDpGJnGVc0dRFzHIhypQmQi0q5cAr6hkP+UAcMyqiN5YdXMFhlF3i2eJPb3q/KUmhBuThBh4iMm7U5bAzsugYNyKCsYtD6gSbcxh4ro/MQRvB6q3JEnwjcDIrbcx5PWYHnusjVxLLHaYBSbxNNXVSULZ5AXkbGbpiqfHY9c5LMyX2axt0np2iQ10he+UU5/UIJrG3lmi+pJWtDACPRwR6dhYjI4uOKV7HduuZz0Cb0OYcCNb1EUhGvm301qzAfpPKSht11vUxO7CujzxJLHe46kmrGDcOdprMRKhFpSuqK9RUy0z8Rb+2Qdb9Hi7yCvXBMYUuDE9lYPgsju3pklMUGwbW9fFMETTQ2BlZXBiPayq2LyhkI5v05hwQuoXeSDgjTpdw50sknR971vUxO7CujxxJK3e4Wnk9EkWd9qu8wRSjZHQliFJlqo10Cuq2VK3HUIetgasiyJBINlMmDwljFk9Eq0XlFfojHofWOTMC+0fXVPgE/wPZyboFktKB8+gpQsaVAX3m4wZVD+U1PDibRMoE+kgFOHNihPNqZSsxhCZNeC0XPyMjnQUcaR7bWSzxSMQCQza2KWxz5olc6InkMuJovdUmQrdCmJ3HJm4351dazDFhvFjXx+zAuj7yI7HcgRyugpKEsBGHoUZIEkaLdX0kSK36vGCV19QFFttVQ/hU8Kmk47e8rSG1YpFIBJaGVkWYIXFspkyuQ0JZZnFEtFpUX3GhRWXTH/Mjqv/g7ih2pmyHHAe1Wolxc7EEip+i9B4hUCBFwR1V20tVUTxCcLaImglwamgrT9KcCOF8MbKVOPE/dcJievyMjHUWTVxnIcQvwVRmc0L7ao7ohV5INiPm+g8WjQnorVAogus8hvNR0vhEmV5pUceEEWNdH7MD6/rIjZRyB75MjpIk1MqMODYVj2a8OePFuj6C6fW3xiZ3+tS1tPW4b+bNqXUJPZX0arzZsbFUIEh4L1IMpaFVEWhIFJspk5c6KJRlFj9EqUVbayp9kRqjIj9mRyrYdcSY5Ie6amUR3WgzpE1UwiJE5NgOg7tEyNBRPEJwRkTPBDg1nJXnSZsTHs4PK1uJE/8TJyymx8/IaGfRmySys1jisYgFU7WpxOas0L6lZgha6IH0MuKw3gpFVwO6W2ErJXTnsZ2PkEYnyvxKizomjBnr+pgdWNdHXiSVOzBlclA0t8MIMeIsFnUxRjPenNFCLATS36/OeDvU5j0aMqaAEGTdnFqlDOpU0lE934SY0kBoEnahc1PvvFeL6DINKO3Q0lhDAs50nT7/WVDxtyL2XBoWyjKLG6LUoqjQ7IHOVKl0JkTdAlhBd+jaIcZU0JmUmM1E2wOkSQ1T9UJ/EQKGR+t38ntAA7YDDPoxg7PoAdDPVS8KyAQ4NdyZP1c+wWDCubGSNitbqXHif7I8w2u5vjIy01lQAI7rLNUSj0VAQ9DgeJibU60OlJblB16ITnoZMeit4W+aUgzdrbixoVJJbLWdrxLn280mygErLeqYMGqs62N2YF0fOZFW7kCMOmHR3AgjVHRG5kDr0WjG5x5jhVpIh3qpFEAkCATsWW5leOyppIMQQ+UdG7LpOAoOX5S0LcAQ4dlIoeGYxUj/AN1Zvg0SZZnFCxFqUa1QFZrRQR9zHzASyuglB6Wu6bsDNs6oR8+oELFVjJpAWZuq9Bgh7PC4hRI1OC8okTPKRzYTYNQgLMPoBIMI5xKVrjAEx/8MCIvpPWRkocRwlpSQuRa2KTushb7oYbvHAm9r6ARWtGG7lTU2AJjOY0J2SDJRDiDumDBurOtjdmBdH/mQVu5Alslc2c6EETs6A2ChbdkjCz8r9xgxwEIi6ICh3pE0AuNtqikwUwygt8BgVYoV4YByO+8oSGWTkqViiJBTkJwQQ6RC+HrkIIlQjGbfB4uyzOKEM7wWlWob2sO6xaWij1mQIifvQQ/b8SkSR/mHGwXH3QJGtUlKWITI6q0lamHmY8oiMhMAXcjoH+yZP5MJBhXONW0XWNlKDYz/WRAW0/vKyCxngUR2Fks8FsFibU6ca2k/yQ17ISqJZcQMbUf9R4qWGprakGHdihwb6kl1Htv5bGnYINifQ1Za5DFh5FjXx+zAuj5yIa3cwSyTA4Y7LowY0dkCWt+UTDCZY+UeIwZcSAFdAG+6fJYBSImQh1CRU/VIjJS7GTfUKp9rh62mqWfkpawEittupJxaMghigYZsh5begM1FitngzQTA5KWeQ0RZZjFClFq0qK7ftGtEpS7AoaYff/f3TfOMc2QQgwMWNfe/mWIQZjjWo3Y9pyl9RggjaCrX3mRwBwF2kUQLznatieMGnQmgBANbIJBRBc+fkwkGF86tXysBzFbixf+0CYvpfWVktrNUTWxnMcRjEUslIJJA4wYP7VWZwSxEJL2MGGD0Hx0+itHzlJOEdKvdHhvozmP6jSnNTN1kNw9aaZHHhDFkXR+zA+uaCankDmyZHFS2M2GEiM4QJcgYBpnco43Z1cZCEhQRGuTRFEVvx0Ug1FTsICAl0J6g3GuDwjsxOkYANQUiPEloACYLwYa0BcsJMQSp0WLUKoP3D4Aoom/Uc6Aoy2wwiFOLNrPQjIcxJi116tE0jLGmiXE6CUfpBGkRrRglodIixTQhxkBL2xo89n+i0meEqCpeg0ionH5RXUHflXz04FxQTWj1JiYTUNEDh2OU3gHDUFbIJRhMODdWUifcyFYixf+MWB8Pg74yMttZAJGd5TQ8DouoHNXanFCyUpwf3EI0ksuITZBMUBQpmQ0R2K2aOTawncfwm4D+tck1hW3nVlrkMWEcWdfHPEdCuQNdJrNlOxVGrOiMzYHWwyyByj3GDHOhZ8QGVRtaBApFRdEDhH9jbks5i9BiC98O5BDqrjhRaqJ06UdkKFpDQ6BHbUBGsYYAgGApUbix4cfAyk7iOVyU62MgiFSLbhct6I7BIiPcVo0OEw9AFYuI3tP1GlNDXZagh29QWqAY04LzZOROY9b1EZcdB82CBuKiQzYiMDibQC06hLCZgKEGmmMbtoUkGGQ4hytpqVa2Eif+R6Mc/fSA7YlanP0iHpC+MjLTWU5AZGc5TyweizgZ2CTwwA9pHJG02yMSyWXEAG5bb1oyAdet2LGB6zz2iBHQIQ07RIlFr7TYY0JaDFd7TDQSb0fyTphW7kCXydRwx4YRIzpDbHukOVzucY4WxEIKXLRqFTbniYAqtbMQwrF7aTVaBbLLSDxO7SybbQeKVpwh7JmuB5wTu+4m5zlorOtjCErRSLWoksLIhlWpLccWOf2+/A0YSqmB77HIWcWtAoSGWpeAJ+4Q4Z/o0HkycicI+VcGRNAkOE9ElOCM0jBkEyr+uEzAUqOTN8AWnmDw4RyuJLRmpBER4n/Cifzr0tg3s3tciA1lc56IKM7CchoywznPSr+tSAehxI5Dahmxxuw/trRiS6O6FT020J0HuUpo/2rm6qFXWrQxYVRZ1xmC9Vs7p+6FaeUOSKWhmSnbyTBiRmeTUjY1R6PFEbnHqEEt9AUKSdGgMggl3Kyw1fS4NXVi5B3BqYkVgAINAUdjipmBhTn/WZNz8FjX/EvRWLWokkLIhlVpmBxt1qSjATCaCCENNLHI2c3SkxpMEVJHrH+4UYzcKc26RgEF1R44Y8DVlGQmgBMMbAILZaIdzplMwiJC/M80kX9o4mVkPXAmj/22Ih1aesiIEyWgW202ROexofqXaQfu/BwhY8KbA+u3XH3ibphU7gBVGkMoM9wRYYQYcTBgALOmaIihdTB4gvaI1Mbw4m/86pkWDzC3pfRicIWtsKZO+oU3RIqHV1SB3RLh+Xzm4kbZl6LxatFK1qK0AayN9ZwsPJ9NJPqA3NYuFxJYNG4+n+e5R/9lNWfQyUsQFNOVdXwmYKpRCQQgRoLBhfMwyPg/AKzRaQOF2dpA8EqTliin3a1o2N5mwknDwM5/srBjwhxL8kvfkXfqXphS7hBQdzNlOxlGApAD2KW+3lrDD19zkWnmHuM1/8Yv5AF2Hzv8oFoaq06ATcAbIiSUHVyRNo/c4s1IBpzJQhONGANDujSpVwKOsYj0H1CcIJG7aBEJHZkJ6ASDJ0aCMXvweu6DCtGt4NiQFmbnD6RdF7yek4wsCrGhhK+7mbI9OuajHkIKzD3GmHV95gCQIHOQYeCi4VBXYIe333ebA8zaTbDOd0BUMnSbx2HMNgqR6YuZ13MQABpk/d8bYQlGWDgPIUL8721nT3qHzrGl2ad3ndWjQNBL+7BidqtwiK2MYaUlzRj+2Os5W/zY8EMMd3QYCQBM0nSnNbJtCjP3GGNezz0XWqdTykVYF3JCmLmgK4qWaL/vNtMgx88ZD0OjkSTrxKshXXVUfhqA5uuORCuDAQDYcUjjAjKBYGIkGGw4D4EW2hdR6/l8vvjdckcDe3NmBbs0tJjdKhx7KxuQ0iDwwrXE67nvMwOvEYEo2+kwQqMtKJt1L9tgqAKDXf5kuNQnJSJAzyFVYeFK+XGAcGGZEx3orgGGaDPlFUVIZM9/dlgvgHgz3wFGEyJIBBLF8rLKJtmmSTSSFD5ftPQa6I2gmgykNJXOVS4TMOI5NB4QI8Fgw3kItNC+uIAe9BHJ8SlDA14BxubMCm4pYUqqEN2KHxvszkN8ofsXtAN3fg5+TBhtXs99nxl4PfdMSCt34MtkO5rzYQTByBY5htzXQAMG107gNiCAR8WP1kR4vfilHsCTYfEAGvSEOyNcOIX0h2ap6YtdxiXOEPpM17FEsP6S4Pl6pehGX5M4qc+jUbekXJ2qo17WaNxcN03hi5a+A70RNGt6KBEiTwjKBKgEY0fpXZQEgwznIdBC8yF8t4h4GdnQYKwOQ3JOMEtR6SEjTpXwbgWgOw+C7V9YMF6HNPSYMJIwbjwz8Hrm44Np5Q50mVwjlO1KUCjHsogZGoQWdEgbxisjfrFLfWHkBGLi4thtaoVoD2hq69rCgUIU6aq2YYuIXhFghu0Ca4h0xyCbVWBLg5z2Npz/MLJo64iUjFad1DBOEXmZdoU00HzJ0negN4JmN/tBUPujgpzuaDKP4zMBQw1biYYmGFQ4D6FWUmhOhO8W0UtGZlP7o0JqZGolvSoz7KXIpJYR94jdrQLGBqLzmM5H9y9eML3SuDFhPLHdeGbg9czJBxPLHei6O1bZHo4yHpiDYtdFSBs/khqoqopmh7zLjmKxXeSQAc3KMKRCobzgmfWmxOiAGZMdr4gtzBBo8yZQAgqU2NIhFzeaASF5wjnnR3hx7qTf3ivLj0h85OOck69a7EDfAw2Ex+54YIMiYnsv7EIw0KYSMD4T6NToeK6TRpuwBKNS4dzGyFY4oTkRvltEXxmZ6SyIyM5iibdR6VVFGJvT8CptSj1zwlqKTnIZcWTANuW6lfKKZo4NXOdBI0ZA/zIFg6SZW2n0mDCeWG48M/B65uWDaeUOXJnMlu1sGDGAAUtjGq+1lcv12/iR0kBl3HWLUCDdQYc84p5DlKAuS9Dojd+1oqISdf5zsdmbUqyksYaQZ7quJBYoMR3ycKM5ECoyrqKSk8qf7ZH5aJNMUGiar1j6DfQyVuNQCmkqYi9RQfWjEKwSri7oBmQCASdtZtVygQkGFc5tYLbCxv+cCN8toq+MzHYWQHRnMcQjQIINsz07CdReBf0nN/BSDySXEUcGb1O2W9ljA9t5DOdjpRFqOjPolRYyJowk2I1nBl7P3HwwodyBKpNjlO1wyLE5YcBaDmOEM+3Ro9vIkdRApd1j39UJSyOaVHPZqiYNbV3oNrt9GtBSBT4J6GjodVBQpKUNIc90/eTOfzYVcnCjmZAtG077Xl6b9r16ZdtXLX0GejM0yzgIA6QKpccSGXS2z0i+zOP4TIBWYxKWYJDh3MLKVioX//MhfLeIvjIy21kA8Z0Fi6dk7p0nAqzNKfzHPnP7rEBLvZBeRhwXvE2r0a2Cxgayt52W8xHS2Mw7ZKWxY8JYgtx4ZuD1zM8HU8kdAuturmwnw4gFDFh62FJVtoEwsI0g4QNVH7FNtUKEASGDmP/CsR5K1HoMc5DPReUohh20IeSZrrMSUyEPN5oHL3QJH6qrS9Uwps6TL1r6DPRUaN4OSNGxMTIgU9OAWxzoTIBWYxOQYPCRn2FDZnHxPx/Cd4voKyMjnEUT31kM8QBsK8TcnJRX5YVe6onUMuLY4G1ajW4VNDaE5LsFCeGkkYLplUaOCaOJduOZgdczRx9MK3egR514ZbsJDlh4KIaDI8o9RpCUBiq9TZuaBTfCwNFYhJ4WfCrpzDnIxsX6lcHRhpBnus5KTIbU3Wg+xH1I6/HaHuwxzfkm4Yt2c5+B3oiZ+uwPjBqs9IKwoyhFIJELyQRoNQRkghEU+SFQmYaK/xkRvltE3xnZVkx6cBYhnkFZZWFuTsarMkMu9UZCGXFkDI+RGN0qaGwIyne3ouGkkYLplcaNCeOJdOOZgdczTx9MK3egR50oZTs3yOCA1VkJjDGzBD2kjh3JDVR10c9pzQoDC3yia4cRSwJPJZ1VAyWbIgxbNJ3kYPPIM10nJRom90subjQL/kVF3tXK54syl5XXdz5lvfi6NdRroCcC4bLggg6o0XExTnBWdmBFvWUCAVaadkYI54SypQbH/wx4hKVmfWdkh52RxXcWQzy9tbV6c3MyXpUb3VKPpJsRG9s60AkoEdzYoJTzndjwm5j9nF1p0ceEsaFz45mB1zNXH0wqd6Bjvx3NoxXoRsDqrGQHR7Eq2hiS3kBVF9WsKTMlpwphRiwJO5V0Vg2WbImwbAEsyxJoHhYTqKZWw+SeSdmN5kW+g6GaZJXLz067urT2/WcuY7ZJauD7Fy39BXouZlbMCdSouBgnOGs7sKK+MgHTysgJhmExo6wGx//keT1CU7O+M7LFzMhiO0uAeFNopbZfJbwqx+jbK8lmxMa2DnUCRgQ3NkgFle/Eht9E7efkSos+JowNz32fE8jcB1PKHejYb0fzaAW6HbCgxgq0VLiX3cjxSnGgqrVaj4OO5WgFUCZ5KumR1HQqSBFSHyKOIZFepx7L5L5J143mRj4NY8zkCCdlBz5cVlbtLkmnGWPN52uWCIE+bnBHu9JiNSouhgfnABE9ZQKmlX0lGHTAD43/+XUtYqTrOyOrVkbWg7Ow4glt1PZjvGpgSTsjlpulx55LjgL2ZqY0xu3n3EqLPSaMUD42I5JW7hA6FkUs0FmxlTCz+7/I76PH65mycyrS2HKDZXrvpOpGcyT/yBigIDUnmy6oekrGQZ28NM+vWZIK9OhOA8a+tw0AfaVDQ+Qsw02P2330y+S3LIY8d6jd/0n8923suCxNS577PkvyaRowKNWYLt1lldVj5fLqtNvVQg+pqcuxoUfmHrkBbWqyz5U8HTqXk02WTYgtiEQQb4J5t61ZYh9g03bweVvKUK/U0AvKULLWg3qEjf5D1xrJPYxXCqa/FcLnAt7sgnoz2af8C5y+IuvVT1/Ock3SV2e9wWAMh8GKHtX+WiO9h/FKwPS3Yv7vq5yeIuv1T0/OclXSU2e9xWAUh0HwqPbXGgk+jFf/pr8hkhbAgvadoYEoxEB/jdNPZJ0A9OMs1yX9dNabDMZxGFQPtz44XG8D1ZsjgQbLgWpNDYQeJbqveK7UkD8gnnKtg3r1myhXvQ/e0GLkVgjp8MT+M85Qkmd5oQ18mgb7zyiztVOa9YQCYw32n7HF8UQW9XEkyAIfwKETe7GgPbTQoh7s8JpzIY1rEn9O7IVJ0MBecLFqt2PabdoANNh/xpi9dJZ6KQg10DRP7D8jTLlXPGlXgZjH/jPGlKXymvgA9p9RplQDehSwpsH+M8IgR03ovXax/4wyHhPIUU3TYP8ZYcpdIffalQYY9p9RpvTca1cbAOw/o4uviZVQaHDl3FwsaI8t5a4GtKYh0ODJub1Y0B5XPDUNSTshceXcXixojy+lskedCwN4f/7+a1/9qng5bEeR89mpw/zTAFAtNiQWtO8v1ZHm2HqezyayWNAu8qXbJLCI/Hw+453zRgqNq6dpWDQCQ7r6VefEsIjUNPcCZccUaVvMB09OPu8FbVnM43C0RYSxoH0HONOqXGw9NMJY0B6qoc41jTAWtGMfb3+CoM2KwdLzHagW0Wjrs7FSNskKEo2bRFO4A6u9Ojw9SfZ5frD0ACVrF42WrObqpI4pi8jNvCAUvsc7P5TKusnTh6h4eows5ikaJclhHeyRROQlWlrRxPTK38aGtKQfXw/pEh6RBiQWtJUdInLySHMS9yhP96Ei3uHqoSLjp+jintAtrojKyd0maDgkx3jfodqjRvuPjDVP3D1XGAva8c9u3cO0m29w9iuj8+k47LWhLH/Na5w/2f1qFYK5Hy8Y52GZ0+uLBe2xzlYhIb6pjinrvWMlhbfHyK1fU4Xws/J0aZU/c9l53RXIWLt8YplBVUfdFdrTXew/lTIWzYl6cmVAqV4qJJ2Uqi4eDNo/c3llghoD32MazpERwqXu1p9CGZfmQfFpmE84JJ+qgR/8gjo4t9X+M99Y0I5ltvk1tavn4zIfDD7OYlAUf6UX1vTivrGgHdOIZV5W4h7WYPH5NN6SiNKOc77mF9SaL+loT34lEbGM0cW6ITaeTzw6Sb0dkqdOaHJRFUsyxD1ANfG2Hfca+DaT3wlPewPmggKj13pQsY3nNAGlBppr4VtNmmupuT8My3tBu0h5vHI5RcW3m9xOUpcmiACQDjEMLQayD8KdDnvtbz295TDGR+fNt0ynNh9yrY4mE859NHkcg2KoAYBPBN9BuZ+8mSy+wplCifxVcICfYk4okweSKdVyYHoNaNNwoFJMOffJBsctqgkaFIWxT+OQe6e6hzT0ohJ5Pfjw/KJmEiXy18EBfpJZoUweRKZVS58JNqBNxIEqU65Rx8nncWeN8xD/MObBvtq+6C+oos/bl/Wd3mJf0kysRP4KGKbmhTJ54JhsbSYY0SSTcqCadu6TDVR07eJtYFy8AwAUrUpJxZO5nS+odk4T7jO9xQC+cFbTvTK4QpkZyuRZirnAB9/m2ebXNOcC6VGgOKfxndKmyvLxdVGNI7cKmdKmbSHd0iiEb0s5oQADWdSce4OisHnG+Aqo6NdaueyqshdWpdTubTgvkQYw9tCiHiq0B9UpsOYZ2yBfG5pfe4lov3ivAZzpMhEK0GC6yec3C6S8QVH4+UBMY8j1dpZZTig0zX/C4LrshHMEc1N4nxd482kx3aGmfkFRyJp4hm4ZrypVlj+4ugJQ53elhiTbUB7l600eb1AUFtpAbCOywe+LMsE559fPwvvp+FW9sPiU3kDgR1uaH8tPlkNV4aXU7p8icXSYFoHF52feAcMG1jRxjO7rVwQ6rPL9PImyx+uVhPV0aldkUOzwydyFsaP8AMTwy8ja5aGV1Yc/1ZEuEXQeEToculh8SmVHz712WRO7ANUktLZ1Hs8wtqsI7auW1MAHk0/pHoVO/UGI3cqVfYeQbagzhsqtQ/vATKkd3c7rTkgT2l+AD1aZ+xEpMLHbpphP+KgX0ut8uEUtyHtaWynnYS4ksPCxL4TDJ0gg8H+eN0byb3sykEX7sruyx8itqo5x5EoNybJRCB32ZE98Pt577XaFdrJxu3o2oQR0y5y02zGdR6tsks6T3d1FUGANhAmQQ1z+6qwJbSBeCakGqOimYS+rMe26xKphyvJsrNxjchKyI9nx+5S74lMn7gboySd5zVWp+LwWq0vdiWI+1K6OdNWGMcD3E4BS8fqu0ICR6+ymYVoJ6SeXVeu1HnaPAdw/Z3e/5pXELCHzoIt5rJABoyJUe6BGdImz2FdWyHCb8PqgUQPTbfKeQLdsrNzilU5QI70AFUviupNkrgHA+BNg3kMJN90HnoiFxLoWkMhW9gG5665rYJg6QYNnMfvs1TEtBRIoY/FKWAuudXW0hQTmj9H9PKoSMe4awP5TquHljRqYO0EDRq8pdxKvV2nOgPo0qL065l4DAOD+UYNfpdrvAs/GPV/zocp9QCsScgZvtUN2O7a9BCeL58e/QTGeqIF53gk+QItsVKVrgVD4nOPz8TGAdBQZ3p/dHrXHxvMZu6swFpbE7nv1ajcKzfMcT8cxWWT+BrD8+LakThs0HJLvAOhJFx2SjmyT8HkGWH3AyMJjoEMM4Pqp+OSd9S7PTwwTwkLNXetpjwQsagCenguxeuvXDp8nlp+94mi3KSP27wPPZ+M5V2pAylOa53k838ghec2R+rX32kCD48czYA4UmiauCWyhRSwkHVqach7UPe/1SOyYbRLLzz682tU7yeXuBg1QsrwqN2XCtRAUxMCWje6SdMLdhNlnsN4767LmnoCMooOTqsNJrl9B8RhoEQPpKrH7pOOrXgqNRgbInWF9lYgFCk0THF8DpU1ydzdWn62d5m7TBrV/Z8hH93z3iIXgK38DNumw++i1Wzf0zrp3BvfVUzVMng+RBMdjwIhuGo56lZh9DCVCU7Td/HeGD1DRpW0u3PwZEn98DIi8zXJBMfubnUUig6J9jzBUC4J2CkBQzjpJXCe/4/QNfT6eEYF63oFViNBGbZrz8T81qCHtHc6WPhlk+sLg63lDwKBOZqyJQAxk/BG4QClQ5NcdFW83w5pgpU9ePXPBAoZDMuJiRDG/HsOg/8xenL+4CunqMcmJQxAn/7c/T+4z2xsYXFS6r+OX59NJAZDb2uVIXVPPOSmaL0/DmIdhWgQRF1W/JP7hkBw/RCgwVEoZvOV43jyAUlZjnS2XVVsfle/0FotZgl5UBH8PGKoXBDWMyXRZvQ6rXMZMUAMQ53xw+TRAydbPytNBZMOFZd3kcKS50BSaZ7wS5JKqGHzA6HXJEoRy3y8+m2/3vfyhLPchmfPCWeJ8hVxRFYOP0X2avPheXpcqPtYZ0tdiMUP0wuBDRTZaW5VXxq4qPi0bhabB/jN4bBnf1X51IKPrgoD9Xw3fl4VHNDf3z4SCdhSO2iQTscP1y2e/Ok8450dI8aHaz3yZZgjrKOd8THOCbr6n8th/jIouC6954sqX6qjn8K4uq5Bwb3HZMZSI0CrWeazOhkPyFtpZT68LYf8ZPL47S2jJLUfbSedK7c6TI82FDO2tMfC5t3jsfD7hLx9qZN+OzmalKqWUtQq9hYyE8Lq/+MnEajgk+wyePj+GSlX84FYpPuXCsNDhkNzcXXx2nmHDIdmIbkIiIqiuR6vsq05f1e6NDqlQDj+fH+w/Q0jodsWB0TkyePp8WpbEYcq6lqu9OtJem7AtrsX+M+CcGR+5Q5VqqLs+T6z7BsVau4s3OqSw/4wZH5DewdPPBVknl1yTbrLe6JDC/jNS+I6J/suig6cvtXf45Oi2vOy+D0mHtBoG+89o0fhYH7PNPxySZZG9qtITG2MMsP+MFOj8Z0BCAncuJPhHBK7uZ65c4ysxThb7zxjxbJghq3fud2jD/KFkTRHjiEcMsP+MEA2A9IQE7pTrAOGQTPLa7q7xQkLzwf4z4ISyULRj5VpYRIBwSPaJjbEkK1wD2H9Ghwbotryqfa/GRVA4HywfYOiGGkgWxAD2n8EmRCKeiS43F4HCIbkB0H17+E58Oew/Y4JbxOJaRywUGj7Ps/jXOfVIc8QA9p8RoQEj+xSxXq/SBA+HZJJ7J76cBvhg/4lKDIZDcjEfFTr3O0KFQ7J34su5xqHB/jMafIBuvnO/owkcHXSue2fmgAf2n5EAsZDYsvTM/Y5AnLkL774PU04MfJ7Y/80jcTXIIrXIRJdD535H8JVroJ8RA3Mvsf+MBmD0muyohQjCIZms9bCXFo2gU+w/o0E+luVQrySicEieBk84JGP/2cfiamelbNJFEw7JqHFe59IA9p99NP6IWOq5EzSqcEjeurntNor9P2RE/oihZBORhkOyEITCd+x/zVLH45mlAhhKTYBwSO4DhkMy6qQB7H+D6qKeUF3sh0NyMC+x/0QlrsMheZmOpCPnebr9Z4j9b0p/5FPpj+9wSF46IYE1gcIhGfs/XjBxXy+Y+A6HZC1p4FvpYv8ZPz4+Y76P/Wek+aAJ+08KxHo4JGP/SYJYD4dk7D9JEOtBcYr9x/3H/Wf24b6GQzL2XyPfsP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+4/7j/uP+8U8Ivwv1v497+Bg==)

有关该 pipeline 中使用的插件的信息，请参见 [Pipeline 流](https://docs.qualcomm.com/doc/80-70018-50SC/topic/camera-detection-display.html#camera-detection-display__section_jbz_cbk_bdc)。

## 运行应用程序

1. 确保您已完成[前提条件](https://docs.qualcomm.com/doc/80-70018-50SC/topic/prerequisites-for-python-sample-applications.html)。
2. 运行各种用例：

Table : 用于目标检测和显示的 python 应用程序的示例模型和标签文件

    | Runtime | 模型 | 标签 |
    | :--- | :--- | :--- |
    | LiteRT | <var class="keyword varname">yolov8_det_quantized.tflite</var> | <var class="keyword varname">yolonas.labels</var> |
    | Qualcomm Neural Processing SDK | <var class="keyword varname">yolonas.dlc</var> | <var class="keyword varname">yolonas.labels</var> |

    - 分别用主摄像头和辅助摄像头进行显示：
        - gst-ai-object-detection.py -c 0 -f 2 -m /etc/models/yolov8_det_quantized.tflite -l /etc/labels/yolov8.labels -ml "yolov8" -k "YOLOv8,q-offsets=<-107.0, -128.0, 0.0>,q-scales=<3.093529462814331, 0.00390625, 1.0>"Copy to clipboard
        - gst-ai-object-detection.py -c 1 -f 2 -m /etc/models/yolov8_det_quantized.tflite -l /etc/labels/yolov8.labels -ml "yolov8" -k "YOLOv8,q-offsets=<-107.0, -128.0, 0.0>,q-scales=<3.093529462814331, 0.00390625, 1.0>"Copy to clipboard
    - 使用视频文件输入进行显示：

            gst-ai-object-detection.py -s /path/to/input/video.mp4 -f 2 -m /etc/models/yolov8_det_quantized.tflite -l /etc/labels/yolov8.labels -ml "yolov8" -k "YOLOv8,q-offsets=<-107.0, -128.0, 0.0>,q-scales=<3.093529462814331, 0.00390625, 1.0>"Copy to clipboard
    - YOLO-NAS with LiteRT：

            gst-ai-object-detection.py -f 2 -m /etc/models/yolonas.tflite -l /etc/labels/yolonas.labels -ml "yolo-nas" -k "YOLO-NAS,q-offsets=<37.0, 0.0, 0.0>,q-scales=<3.416602611541748, 0.00390625, 1.0>"Copy to clipboard
    - 带有 Qualcomm Neural Processing SDK runtime 的 YOLO-NAS：

            gst-ai-object-detection.py -f 1 -m /etc/models/yolonas.dlc -l /etc/labels/yolonas.labels -ml "yolo-nas" --layers="/heads/Mul,/heads/Sigmoid"Copy to clipboard
    - YOLOv8 与 LiteRT：

            gst-ai-object-detection.py -f 2 -m /etc/models/yolov8.tflite -l /etc/labels/yolov8.labels -ml "yolov8" -k "YOLOv8,q-offsets=<-107.0, -128.0, 0.0>,q-scales=<3.093529462814331, 0.00390625, 1.0>"Copy to clipboard

如需显示可用的帮助选项，可运行以下命令：

gst-ai-object-detection.py -hCopy to clipboard

## 预期输出

Figure : 目标检测和显示应用程序的预期输出 - 预览
                
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)

## Pipeline 流

| 处理过程 | 说明 |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtiqmmfsrc.html) | <ol class="ol" id="camera-detection-display__ol_l2f_zgm_vbc"><br>                                    <li class="li">采集视频流（源）并创建源的两个副本：<ul class="ul" id="camera-detection-display__ol_m2f_zgm_vbc"><br>                                            <li class="li">一个视频流被发送到 <a href="https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtimetamux.html">qtimetamux</a> 插件以保留视频流。</li><br><br>                                            <li class="li">另一个视频流被发送到 ML 推理 pipeline。</li><br><br>                                        </ul><br></li><br><br>                                </ol> |
| filesrc | 读取视频数据。 |
| **预处理** | **预处理** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtimlvconverter.html) | <ol class="ol" id="camera-detection-display__ol_xsf_q5l_vbc"><br>                                    <li class="li">在其接收端口上接收视频流。</li><br><br>                                    <li class="li">执行预处理：<ul class="ul" id="camera-detection-display__ul_ff2_twl_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">在模型需要浮点值作为输入时，对流数据进行归一化</li><br><br>                                        </ul><br></li><br><br>                                    <li class="li">在其发送端口上将视频流转换为张量数据。<p class="p">目标检测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/80-70018-50SC/topic/qtimltflite.html) | <ol class="ol" id="camera-detection-display__ol_ufn_2lm_vbc"><br>                                    <li class="li">加载目标检测模型。</li><br><br>                                    <li class="li">为选择的 delegate 修改图。</li><br><br>                                    <li class="li">在其接收端口上接收张量数据。</li><br><br>                                    <li class="li">运行推理并在其发送端口上生成带有目标检测结果的张量数据。</li><br><br>                                </ol> |
| **后处理** | **后处理** |
| [qtimlvdetection](https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtimlvdetection.html) | <ol class="ol" id="camera-detection-display__ol_w4p_bck_bdc"><br>                                    <li class="li"> 接收来自目标检测的推理张量。 </li><br><br>                                    <li class="li">将其接收端口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-detection-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 的接收端口。</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtimetamux](https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtimetamux.html) | <ol class="ol" id="camera-detection-display__ol_ll3_x5l_vbc"><br>                                    <li class="li">在接收端口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">使用接收端口上的视频流内容生成 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发送端口上的 GST 缓存元数据（元复用）。</li><br><br>                                </ol> |
| [qtivoverlay](https://docs.qualcomm.com/doc/80-70018-50SC/topic/qtioverlay.html) | <ol class="ol" id="camera-detection-display__ol_wst_y5l_vbc"><br>                                    <li class="li">接收复用流。</li><br><br>                                    <li class="li">使用 CL 将边框叠加在 VideoFrame 上。 </li><br><br>                                    <li class="li">在其发送端上口生成带有叠加层的 GST 缓存。</li><br><br>                                </ol> |
| **输出** | **输出** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70018-50SC/topic/waylandsink.html) | <ol class="ol" id="camera-detection-display__ol_dyv_1lm_vbc"><br>                                    <li class="li">在其接收端口上接收视频流。</li><br><br>                                    <li class="li">将视频流提交到 Weston。 </li><br><br>                                    <li class="li">Weston 在本地显示设备上对该场景的目标对象生成的视频流和边框进行渲染。</li><br><br>                                </ol> |
| Filesink | 将视频写入文件。 |

**Parent Topic:** [Python 应用程序](https://docs.qualcomm.com/doc/80-70018-50SC/topic/python-sample-applications.html)

**Related Resources**  

- [目标检测](https://docs.qualcomm.com/doc/80-70018-50SC/topic/gst-ai-object-detection.html)

Last Published: Nov 12, 2025

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