fix tflitemicro_person_detection
This commit is contained in:
yangqingsheng
@@ -2,11 +2,11 @@
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**作者：**
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Github ID: [Derekduke](https://github.com/Derekduke) E-mail: dkeji627@gmail.com
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Github: [Derekduke](https://github.com/Derekduke) E-mail: dkeji627@gmail.com
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Github ID: [QingChuanWS](https://github.com/QingChuanWS) E-mail: bingshan45@163.com
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Github: [QingChuanWS](https://github.com/QingChuanWS) E-mail: bingshan45@163.com
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Github ID: [yangqings](https://github.com/yangqings) E-mail: yangqingsheng12@outlook.com
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Github: [yangqings](https://github.com/yangqings) E-mail: yangqingsheng12@outlook.com
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## 概述
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@@ -50,7 +50,7 @@ Github ID: [yangqings](https://github.com/yangqings) E-mail: yangqingsheng12@ou
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有三种方式获取tflite_micro：
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1. 从TencentOS tiny 代码仓库 `components\ai\tflite_micro`目录获取；
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2. 以lib文件的形式使用tflite_micro组件，lib文件`TencentOS-tiny\components\ai\tflite_micro`的ARM_CortexM4_lib、ARM_CortexM7_lib和ARM_CortexM55_lib文件夹
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2. 以lib文件的形式使用tflite_micro组件，lib文件`TencentOS-tiny\components\ai\tflite_micro`的ARM_CortexM4_lib、ARM_CortexM7_lib和ARM_CortexM55_lib文件夹；
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3. 从Tensorflow代码仓库获取，TFlite_Micro的源码已经开源，github仓库地址为：https://github.com/tensorflow/tensorflow ，可根据google TFLite Micro官方教程获得Tensorflow Lite Micro的全部源码。
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如果没有tflite_micro开发经验，建议以**第一种**或者**第二种**方式获取tflite_micro，希望自行获取最新源码，或者编译lib文件，请参考`TencentOS-tiny\components\tflite_micro`目录的TFlite_Micro_Component_User_Guide.md文档，本指南将直接使用TencentOS tiny 代码仓库内的tflite_micro组件。
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@@ -62,12 +62,13 @@ Github ID: [yangqings](https://github.com/yangqings) E-mail: yangqingsheng12@ou
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以下是整个例程的目录规划：
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| 一级目录 | 二级目录 | 三级目录 | 说明 |
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| :-------: | :--------------------------: | :----------: | :----------------------------------------------------------: |
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| :-------: | :--------------------------: | :-------------------: | :----------------------------------------------------------: |
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| arch | arm | | TencentOS tiny适配的IP核架构（含M核中断、调度、tick相关代码） |
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| board | NUCLEO_STM32L496ZG | | 移植目标芯片的工程文件 |
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| | | BSP | 板级支持包，外设驱动代码在Hardware目录 |
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| component | ai | tflite_micro | tflite_micro源码 |
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| component | ai | tflite_micro | tflite_micro源码及有关库文件 |
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| examples | tflitemicro_person_detection | | 行人检测demo示例 |
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| | | tflu_person_detection | 行人检测实例代码 |
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| kernel | core | | TencentOS tiny内核源码 |
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| | pm | | TencentOS tiny低功耗模块源码 |
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| osal | cmsis_os | | TencentOS tiny提供的cmsis os 适配 |
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@@ -209,9 +210,9 @@ void task1(void *arg)
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其中，retarget.c的路径为：`TencentOS-tiny\components\ai\tflite_micro\KEIL\retarget.c`
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tensorflow_lite_micro.lib的路径为：`TencentOS-tiny\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow_lite_micro.lib`
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tensorflow_lite_micro.lib的路径为：`TencentOS-stiny\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow_lite_micro.lib`
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其余.cc文件均在当前目录下的`tflu_person_detection`文件夹中。
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其余.cc文件和.h均在`examples\tflu_person_detection\tflu_person_detection`文件夹中。
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#### 1.3 关闭Keil的MicroLib库
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@@ -243,7 +244,7 @@ TencentOS-tiny\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow\lite\micro
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本例程的任务函数在
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`TencentOS-tiny\examples\tflitemicro_person_detection\tflitemicro_person_detection.c`目录下
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`TencentOS-tiny\examples\tflitemicro_person_detection\tflitemicro_person_detection.c`
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#### 2.1 图像预处理
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@@ -311,13 +312,13 @@ void task2(void *arg)
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#### 2.3 运行效果
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通过串行输出实时打印信息，移动摄像头，镜头没有对准行人时，输出如下：
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通过串行输出实时打印信息，移动摄像头，没有对准行人时，输出如下：
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<div align=center>
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<img src="./image/reasult_no_person.png" width=70% />
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</div>
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当镜头对准行人时，输出如下：
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当摄像头对准行人时，输出如下：
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<div align=center>
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<img src="./image/reasult_person.png" width=70% />
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@@ -1,23 +0,0 @@
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## TencentOS-tiny_Person_Detection_Demo
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### 1. 目录结构：
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- TencentOS-tiny\board\NUCLEO_STM32L496ZG\BSP\Hardware : **外设驱动代码**
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- TencentOS-tiny\examples\tflitemicro_person_detection : **Demo任务函数**
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- TencentOS-tiny\board\NUCLEO_STM32L496ZG\KEIL\tflitemicro_person_detection : **keil工程**
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- TencentOS-tiny\components\tflite_micro\tensorflow : **tflite_micro代码**
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### 2. 完成的工作：
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- 使用STM32CubeMX，选择与TOS同版本的固件库重新生成外设初始化代码；
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- TOS、摄像头和LCD工作都正常工作；
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- tflite_micro 以component的形式加到工程
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- retarget.c引入工程，并通过宏进行选择
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- example中行人检测demo已经可以正常工作
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### 3. 未完成的工作：
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- 变量名、函数名还没有按照TOS的风格完全统一
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- keil移植指南
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- tflite_micro用户指南
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File diff suppressed because it is too large
Load Diff
@@ -137,7 +137,7 @@
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<DriverSelection>4107</DriverSelection>
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</Flash1>
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<bUseTDR>1</bUseTDR>
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<Flash2>STLink\ST-LINKIII-KEIL_SWO.dll</Flash2>
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<Flash2>BIN\UL2CM3.DLL</Flash2>
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<Flash3></Flash3>
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<Flash4></Flash4>
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<pFcarmOut></pFcarmOut>
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@@ -339,7 +339,7 @@
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<MiscControls></MiscControls>
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<Define>USE_HAL_DRIVER,STM32L496xx,NUCLEO_STM32L496ZG</Define>
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<Undefine></Undefine>
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<IncludePath>..\..\BSP\Inc;..\..\..\..\platform\vendor_bsp\st\STM32L4xx_HAL_Driver\Inc;..\..\..\..\platform\vendor_bsp\st\STM32L4xx_HAL_Driver\Inc\Legacy;..\..\..\..\platform\vendor_bsp\st\CMSIS\Device\ST\STM32L4xx\Include;..\..\..\..\platform\vendor_bsp\st\CMSIS\Include;..\..\..\..\arch\arm\arm-v7m\common\include;..\..\..\..\arch\arm\arm-v7m\cortex-m4\armcc;..\..\..\..\kernel\core\include;..\..\..\..\kernel\pm\include;..\..\..\..\osal\cmsis_os;..\..\..\..\examples\hello_world;..\..\TOS_CONFIG;..\..\..\..\net\at\include;..\..\..\..\kernel\hal\include;..\..\BSP\Hardware\Inc;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\flatbuffers\include;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\gemmlowp;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\kissfft;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\ruy;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow\lite\micro\tools\make\downloads</IncludePath>
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<IncludePath>..\..\BSP\Inc;..\..\..\..\platform\vendor_bsp\st\STM32L4xx_HAL_Driver\Inc;..\..\..\..\platform\vendor_bsp\st\STM32L4xx_HAL_Driver\Inc\Legacy;..\..\..\..\platform\vendor_bsp\st\CMSIS\Device\ST\STM32L4xx\Include;..\..\..\..\platform\vendor_bsp\st\CMSIS\Include;..\..\..\..\arch\arm\arm-v7m\common\include;..\..\..\..\arch\arm\arm-v7m\cortex-m4\armcc;..\..\..\..\kernel\core\include;..\..\..\..\kernel\pm\include;..\..\..\..\osal\cmsis_os;..\..\..\..\examples\hello_world;..\..\TOS_CONFIG;..\..\..\..\net\at\include;..\..\..\..\kernel\hal\include;..\..\BSP\Hardware\Inc;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\flatbuffers\include;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\gemmlowp;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\kissfft;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\third_party\ruy;..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow\lite\micro\tools\make\downloads;..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection</IncludePath>
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</VariousControls>
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</Cads>
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<Aads>
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@@ -778,31 +778,6 @@
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<Group>
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<GroupName>tensorflow</GroupName>
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<Files>
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<File>
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<FileName>person_detect_model_data.cc</FileName>
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<FileType>8</FileType>
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<FilePath>.\tflu_person_detection\person_detect_model_data.cc</FilePath>
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</File>
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<File>
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<FileName>model_settings.cc</FileName>
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<FileType>8</FileType>
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<FilePath>.\tflu_person_detection\model_settings.cc</FilePath>
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</File>
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<File>
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<FileName>main_functions.cc</FileName>
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<FileType>8</FileType>
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<FilePath>.\tflu_person_detection\main_functions.cc</FilePath>
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</File>
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<File>
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<FileName>image_provider.cc</FileName>
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<FileType>8</FileType>
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<FilePath>.\tflu_person_detection\image_provider.cc</FilePath>
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</File>
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<File>
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<FileName>detection_responder.cc</FileName>
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<FileType>8</FileType>
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<FilePath>.\tflu_person_detection\detection_responder.cc</FilePath>
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</File>
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<File>
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<FileName>retarget.c</FileName>
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<FileType>1</FileType>
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@@ -813,6 +788,31 @@
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<FileType>4</FileType>
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<FilePath>..\..\..\..\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow_lite_micro_M4.lib</FilePath>
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</File>
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<File>
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<FileName>detection_responder.cc</FileName>
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<FileType>8</FileType>
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<FilePath>..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection\detection_responder.cc</FilePath>
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</File>
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<File>
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<FileName>image_provider.cc</FileName>
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<FileType>8</FileType>
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<FilePath>..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection\image_provider.cc</FilePath>
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</File>
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<File>
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<FileName>main_functions.cc</FileName>
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<FileType>8</FileType>
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<FilePath>..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection\main_functions.cc</FilePath>
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</File>
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<File>
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<FileName>model_settings.cc</FileName>
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<FileType>8</FileType>
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<FilePath>..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection\model_settings.cc</FilePath>
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</File>
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<File>
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<FileName>person_detect_model_data.cc</FileName>
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<FileType>8</FileType>
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<FilePath>..\..\..\..\examples\tflitemicro_person_detection\tflu_person_detection\person_detect_model_data.cc</FilePath>
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</File>
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</Files>
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</Group>
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<Group>
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@@ -1,3 +1,13 @@
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/**
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* @file tflitemicro_person_detection.c
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* @author Derekduke (dkeji627@gmail.com); QingChuanWS (bingshan45@163.com); yangqings (yangqingsheng12@outlook.com)
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* @brief Person detection example based on TencentOS-Tiny and TFlite_Micro.
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* @version 0.1
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* @date 2021-01-05
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* @copyright Copyright (c) 2021
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*
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*/
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#include "cmsis_os.h"
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#include "mcu_init.h"
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@@ -37,7 +47,7 @@ void task1(void *arg)
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{
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while (1) {
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if(frame_flag == 1){
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printf("*person_detect_task\r\n");
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if(HAL_DCMI_Stop(&hdcmi))Error_Handler(); //stop DCMI
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input_convert(camera_buffer,model_buffer);
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person_detect(model_buffer);
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@@ -55,8 +65,8 @@ void task1(void *arg)
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void task2(void *arg)
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{
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while (1) {
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printf("***person detection task\r\n");
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osDelay(50);
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//printf("***task2\r\n");
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osDelay(200);
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}
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}
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