Public datasets are valuable for the development of the learning-based algorithms. In the field of autonomous driving, almost all the existing public datasets are collected by manually driving cars, and most of them are contributed by American and European researchers and represent the traffic scenarios typical for these countries. To diversify the public driving datasets and to provide data support for researches on the self-driving vehicles moving on bike lanes, such as wheelchairs, bikes, and some robots, we present the Chinese Driving from a Bike View (CDBV), which is a driving dataset collected by a bike in Beijing, China. The CDBV dataset contains annotated images, raw videos, and code tools. The annotations are for the object detection tasks and especially focus on the categories with Chinese characteristics, including the express tricycles, the motorbikes specializing in takeouts, the bicycle landmarks, the zebra crossings, and the traffic lights. We totally annotated 40 064 traffic elements in 13 427 images. The CDBV dataset is publicly available at http://sujingwang.name/CDBV.html.