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The project bases on keras to detecte the driver's actions which are correct or dangerous, thank you for your reading

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Driver-detection

The project bases on keras to detect the driver's actions which are correct or dangerous, thank you for your reading The project will use the VGG , ResNet and MobileNet_v1 to detect the driver datasets. The project running the pycharm, so for the .sh file you should use the Git (recommend).

1.my_models directory

  In the directory, you can get the VGG models ,ResNet models, and MobileNet_v1 based on the keras or tensorflow.

2.picture_data directory

  This is a result. when you run the code ,you can get the result in here.

3.state-farm-distracted-driver-detection directory

  There are your datasets 
  dowmloading from https://www.kaggle.com/competitions/state-farm-distracted-driver-detection/data.

4. 0_train.sh

  This is a .sh file ,you should run it for training the models

5. 1_test.sh

  This is a .sh file too, you can run it for testing the models.

6. main.py

  The file is the important, you can change something you want.
  In the here , you should pay attention to your datasets、models... 's file path!!!!

7.Draw_picture_train1.py(may be unnecessary for reader,the file just to me!!!)

  The file is about show many result after training the model and saving it.

8.data_argument.py(may be unnecessary for reader,the file just to me!!!)

  This is about the process from data.

9.tflite.py

  If you want to create a app or use MCU、CPU which is removable,you need run the code to transform your models.

10.myqtpy5.py

  The project is to predict a picture which on your computer and to show the result.

Application(if you want to use the model running into a app, you should look the topic!!!)

  https://github.com/yeyupiaoling/ClassificationForAndroid/tree/master/TFLiteClassification
  and 
  https://resource.doiduoyi.com/#c1uo2s4
  
  The above is important for the app created, and we can run the two projects to load ourselves' models in the mobile phone.
  我制作的app核心代码全部来自于这两个网址,处于诚实且保护原作者成果的原则,只贴附上原作者代码。
  以下两点是其中修改符合自己模型的处理:
  1.  第一个网址的代码中:注意自己tflite的输入层和输出层的名字是否一致数据部分。记得修改均值为0,方差为255f!(这里根据读者预处理决定)
  2.  第二个网址的代码中:因为是10个类别,需要修改数组大小,本人网络训练预处理预处理用的是除以255f,因此这里也需要这么处理!

Summary

  This is my first create project in the github, If you can see here ,thank you!!.
  The project is my undergraduate graduation thesis's code, and I want to remenber the beautiful time.

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The project bases on keras to detecte the driver's actions which are correct or dangerous, thank you for your reading

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