Cityscapes
The Cityscapes format is a widely-used standard in the field of computer vision, particularly for tasks involving semantic and instance segmentation in urban scenes. This dataset format typically comprises high-resolution images of cityscapes along with detailed pixel-level annotations.
Each pixel is labeled with a category such as “road,” “pedestrian,” or “vehicle,” making it a valuable resource for training and validating machine learning models aimed at understanding urban environments. It’s a go-to choice for researchers and professionals working on autonomous vehicles, robotics, and smart cities.
For more information, see:
Cityscapes export
For export of images:
- Supported annotations: Polygons (segmentation), Bounding Boxes.
- Attributes:
is_crowd
boolean, should be defined for labels ascheckbox
. Specifies if the annotation label can distinguish between different instances. If False, the annotation id field encodes the instance id.
- Tracks: Not supported.
The downloaded file is a .zip archive with the following structure:
.
├── label_color.txt
├── gtFine
│ ├── <subset_name>
│ │ └── <city_name>
│ │ ├── image_0_gtFine_instanceIds.png
│ │ ├── image_0_gtFine_color.png
│ │ ├── image_0_gtFine_labelIds.png
│ │ ├── image_1_gtFine_instanceIds.png
│ │ ├── image_1_gtFine_color.png
│ │ ├── image_1_gtFine_labelIds.png
│ │ ├── ...
└── imgsFine # if saving images was requested
└── leftImg8bit
├── <subset_name>
│ └── <city_name>
│ ├── image_0_leftImg8bit.png
│ ├── image_1_leftImg8bit.png
│ ├── ...
label_color.txt
a file that describes the color for each label
# label_color.txt example
# r g b label_name
0 0 0 background
0 255 0 tree
...
*_gtFine_color.png
class labels encoded by its color.*_gtFine_labelIds.png
class labels are encoded by its index.*_gtFine_instanceIds.png
class and instance labels encoded by an instance ID. The pixel values encode class and the individual instance: the integer part of a division by 1000 of each ID provides class ID, the remainder is the instance ID. If a certain annotation describes multiple instances, then the pixels have the regular ID of that class
Cityscapes annotations import
Uploaded file: a zip archive with the following structure:
.
├── label_color.txt # optional
└── gtFine
└── <city_name>
├── image_0_gtFine_instanceIds.png
├── image_1_gtFine_instanceIds.png
├── ...
Creating task with Cityscapes dataset
Create a task with the labels you need or you can use the labels and colors of the original dataset. To work with the Cityscapes format, you must have a black color label for the background.
Original Cityscapes color map:
Upload images when creating a task:
images.zip/
├── image_0.jpg
├── image_1.jpg
├── ...
After creating the task, upload the Cityscapes annotations as described in the previous section.