Cityscapes Dataset
Cityscapes Dataset is a reference dataset for computer vision applied to urban environments. It offers a valuable base of annotated images for the segmentation and analysis of street scenes, particularly useful in the field of autonomous vehicles.
Approximately 5,000 high-resolution images in PNG format, annotations in JSON
Usable for academic research purposes under a specific license (Cityscapes Research License)
Description
The dataset contains approximately 5,000 high-resolution images with extensive annotations for:
- Semantic segmentation (classes like road, sidewalk, building, pedestrian, car, etc.)
- Instance segmentation (individual objects with precise contours)
- Object detection and recognition in complex urban environments
The annotations are provided in JSON format, compatible with the main Computer Vision frameworks, thus facilitating the training of models in contexts of heavy traffic or varied infrastructures.
What is this dataset for?
Cityscapes Dataset is primarily used for:
- Training image segmentation models in urban environments
- Street scene analysis for the perception of autonomous vehicles
- Recognizing objects and behaviors in urban traffic
- The study of the road context to improve the safety and navigation of intelligent systems
Can it be enriched or improved?
Yes, although already very precise, Cityscapes can be enriched by:
- The addition of images from other continents or climates to broaden the diversity of the dataset
- The creation of new categories adapted to specific contexts (service vehicles, urban furniture, etc.)
- Combining with other datasets such as Mapillary or BDD100K to increase geographic and contextual coverage
- The use of platforms such as CVAT or Label Studio to adapt or refine annotations according to research or implementation needs
🔗 Source: Cityscapes Dataset
Frequently Asked Questions
Is the Cityscapes dataset suitable for real-time deep learning?
Yes, although the images are in high resolution, it is possible to resize or extract subregions that are relevant for learning in real time. Many lightweight models use Cityscapes for pre-training or validation.
What are the main differences between Cityscapes and BDD100K?
Cityscapes is very accurate but limited to European scenes, while BDD100K covers more varied scenes (including nighttime) and integrates more metadata (weather conditions, road type, etc.). The two datasets are often complementary.
Can Cityscapes be used for commercial projects?
No, the dataset is for academic use only. For commercial projects, it is necessary to request a special license or to opt for an open source dataset for explicit commercial use.
