Urban Surveillance Dataset – 8,085 Groups, 10 Categories with Bounding Box Annotations

urban surveillance dataset

city management dataset

urban object detection dataset

public space monitoring dataset

smart city dataset

urban environment dataset

This dataset contains 8,085 groups of images across 10 categories The collection scenes include street, snack street, shop entrance, corridor, community entrance, construction site, etc. The data diversity includes multiple scenes, different time periods(day, night), different photographic angles. Each image is annotated with rectangular bounding boxes for urban objects. This data can be used for tasks such as urban object detection, smart city management, public safety monitoring, and AI-driven city infrastructure analysis.

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Specifications

Data size

10 categories, including 18 subclasses, a group of data contains 2 images from different angles and 1 video

Collecting environment

including street, snack street, shop entrance, corridor, community entrance, construction site, etc.

Data diversity

multiple scenes, different time periods, different photographic angles

Device

cellphone

Collecting angle

looking down angle

Collecting time

day, night

Data format

the image data format is .jpg, the video data format is .mp4, .mov, the annotation file format is .json

Annotation content

the urban refined management categories in the images were annotated with rectangular bounding boxes

Accuracy rata

the error bound of each vertex of quadrilateral bounding box is within 3 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 95%; the accuracy of label annotation is not less than 95%

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