bobdeng1974 / state-farm-distracted-driver-detection

Automatically classification of each driver's behavior given a dataset of 2D dashboard camera images.

State Farm Distracted Driver Detection

Description

The objective of this task is to classify each driver's behavior. The dataset used is from the Kraggle competition: https://www.kaggle.com/c/state-farm-distracted-driver-detection.

This project was made using mainly PyTorch and some Deep Neural Networks with operations optimized by GPU. The convolutional neural networks architectures usede are presented below:

• ResNet

• InceptionV3

• DenseNet

Requirements

• Python 3.6+

• Jupyter Notebook 5.0+

• Numpy 1.13.1+

• Matplotlib 2.0.2+

• PyTorch 0.2.0_3 +

Installation

This notebook was developed in Jupyter Notebook using Anaconda environment. This is not a requirement to run the notebook provided in this repository, however as it was used to develop it therefore it and it is a well known environment among data scientists is provided a quick guide in how to install and set up your environment.

Anaconda

Go to Anaconda download web page and download the version best suited to your platform.

The Installation process is quite simple just follow the assistant that is provided when it is launched the application.

After the installation is done open a terminal and check the version installed using the following code via terminal :

$ conda -V

Then check for the packages using the following :

$ conda list

Check for the versions of listed on Requirements sessions and in case that is something out of data except for Keras that is not a default package use the following code via terminal.

$ conda update anaconda

Pytorch

Go to the pytorch web page and choose the version of the libraries installed on your system. It is important that they folllow the packages version described on Requriments section.

After installing conda, use the following code via terminal.

$ conda install pytorch torchvision cuda80 -c soumith