删除m55库，完善md文档
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QingChuanWS
@@ -191,7 +191,7 @@ void task1(void *arg)
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### 1. tflite_micro组件加入到keil工程
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由于NUCLEO-L496ZG芯片中的内核为ARM Cortex M4，所以本次我们可以直接使用ARM Cortex M4版本的tensorflow_lite_micro.lib库来简化tflite_micro搭建流程。
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由于 NUCLEO-L496ZG 芯片中的内核为 ARM Cortex M4，所以本次我们可以直接使用 ARM Cortex M4 版本的tensorflow_lite_micro.lib 库来简化 tflite_micro 搭建流程。
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#### 1.1 在project中加入新的文件夹tensorflow
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@@ -237,7 +237,7 @@ TencentOS-tiny\components\ai\tflite_micro\ARM_CortexM4_lib\tensorflow\lite\micro
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<img src="./image/tflu_STM32496宏.png" width=80% />
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</div>
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其中宏`NUCLEO_STM32L496ZG`是指定Nucleo STM32L496的hlpuart1为系统printf函数的输出串口，具体定义在Nucleo STM32L496的BSP文件夹中的`mcu_init.c`中。
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其中宏`NUCLEO_STM32L496ZG`是指定 Nucleo STM32L496 的 hlpuart1 为系统 printf 函数的输出串口，具体定义在 Nucleo STM32L496 的 BSP 文件夹中的`mcu_init.c`中。
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### 2. 编写Person_Detection 任务函数
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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
@@ -16,8 +16,8 @@
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<TargetCommonOption>
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<Device>STM32L496ZGTx</Device>
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<Vendor>STMicroelectronics</Vendor>
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<PackID>Keil.STM32L4xx_DFP.2.4.0</PackID>
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<PackURL>http://www.keil.com/pack/</PackURL>
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<PackID>Keil.STM32L4xx_DFP.2.5.0</PackID>
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<PackURL>https://www.keil.com/pack/</PackURL>
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<Cpu>IRAM(0x20000000-0x2004FFFF) IROM(0x8000000-0x80FFFFF) CLOCK(8000000) FPU2 CPUTYPE("Cortex-M4")</Cpu>
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<FlashUtilSpec></FlashUtilSpec>
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<StartupFile></StartupFile>
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@@ -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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@@ -779,24 +779,9 @@
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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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<FileName>tensorflow_lite_micro_M4.lib</FileName>
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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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@@ -804,14 +789,24 @@
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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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<FilePath>..\..\..\..\components\ai\tflite_micro\KEIL\retarget.c</FilePath>
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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>tensorflow_lite_micro_M4.lib</FileName>
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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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<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>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>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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</Files>
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</Group>
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