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chunyexixiaoyu 38d2cb3c85 APP_Framework/Framework/:update knowing framework 
1.fix some Kconfig file
2.add tensorflow-lite-for-mcu in knowing file
3.add mnist application,note the application cannot be used with RAM less than 500K.
4.the version need to separate application and OS(rtt),later by using add transform layer to solve it.
 		2021-07-20 14:50:50 +08:00
..
tools APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
.gitignore APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
K210 mnist .png APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
Kconfig APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
README.md APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
SConscript APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
digit.h APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
main.cpp APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00
model.h APP_Framework/Framework/:update knowing framework 2021-07-20 14:50:50 +08:00

README.md

MNIST 说明

要使用本例程，MCU RAM必须至少500K左右，所以本例程目前在K210上面验证过，stm32f407 目前在rtt上原则上只能采取dlmodule加载的方式。

![K210 mnist ](E:\XIUOS_FRAMEWORK\xiuos\APP_Framework\Applications\knowing_app\mnist\K210 mnist .png)

使用

tools/mnist-train.py 训练生成 mnist 模型。

tools/mnist-inference.py 使用 mnist 模型进行推理。

tools/mnist-c-model.py 将 mnist 模型转换成 C 的数组保存在 model.h 中。

tools/mnist-c-digit.py 将 mnist 数据集中的某个数字转成数组保存在 digit.h 中。

参考资料

https://tensorflow.google.cn/lite/performance/post_training_quantization

https://tensorflow.google.cn/lite/performance/post_training_integer_quant

https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/hello_world/train/train_hello_world_model.ipynb