Sharing and analyzing image data from ubiquitous urban cameras must enable us to understand and predict various contexts of the city. Meanwhile, since such image data always contains privacy data such as people and cars, we cannot easily share and analyze the data through the Internet for the viewpoint of privacy protection. As a result, most of the urban image data are only kept/shared within the camera owners or even discarded to reduce risks of privacy data leakage. To solve the privacy problem and accelerate the sharing of urban image data, we proposed GANonymizer that automatically detects and removes objects related to privacy from the urban images. In this Pitch, we introduce GANonymizer and its performance and show the potential of urban images and videos.