데이터셋 탐색

该数据集是一个全面而多样化的驾驶员行为监测数据集，其中包括来自美洲，亚洲和非洲的26名不同种族，肤色和性别(13名男性和13名女性)的参与者。数据集中的所有图像都是由固定在汽车仪表板上的摄像头拍摄的，所有图像都是RGB像素。该数据集共包含22424张图像。

We've all been there: a light turns green and the car in front of you doesn't budge. Or, a previously unremarkable vehicle suddenly slows and starts swerving from side-to-side. When you pass the offending driver, what do you expect to see? You certainly aren't surprised when you spot a driver who is texting, seemingly enraptured by social media, or in a lively hand-held conversation on their phone. According to the CDC motor vehicle safety division, one in five car accidents is caused by a distracted driver. Sadly, this translates to 425,000 people injured and 3,000 people killed by distracted driving every year. State Farm hopes to improve these alarming statistics, and better insure their customers, by testing whether dashboard cameras can automatically detect drivers engaging in distracted behaviors. Given a dataset of 2D dashboard camera images, State Farm is challenging Kagglers to classify each driver's behavior. Are they driving attentively, wearing their seatbelt, or taking a selfie with their friends in the backseat?