Autonomous vehicles use cameras as one of the primary sources of information about the environment. Adverse weather conditions such as raindrops, snow, mud, and others, can lead to various image artifacts. Such artifacts significantly degrade the quality and reliability of the obtained visual data and can lead to accidents if they are not detected in time. We present an ongoing work on a new dataset for training and assessing vision algorithms' performance for different tasks of image raindrops detection on either camera lens or windshield. At the moment, it contains 8190 images, of which 3390 contain raindrops. Images were labeled by outlining artifacts with polygons. Labeling results are stored in JSON format. Besides, binary masks were generated from this markup, which are also presented in the dataset for convenience. White color denotes an artifact area. For a fast download please use zenodo-get. To install it use the following commands: pip install zenodo-get zenodo_get https://zenodo.org/record/4680442 --output-dir=RaindropsOnWindshield

{"references": ["Vera Soboleva and Oleg Shipitko. \"Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection Algorithm\". arXiv preprint https://arxiv.org/abs/2104.05078 (2021)"]}