PASCAL Visual Object Classes Challenge 2012 (Segmentation Part) is a dataset for instance segmentation, semantic segmentation, and object detection tasks. It is applicable or relevant across various domains.

The dataset consists of 7282 images with 19694 labeled objects belonging to 21 different classes including neutral, person, chair, and other: car, cat, dog, bird, bottle, sofa, aeroplane, pottedplant, train, diningtable, motorbike, tvmonitor, bus, boat, horse, bicycle, cow, and sheep.

Images in the PASCAL VOC 2012 dataset have pixel-level instance segmentation annotations. Due to the nature of the instance segmentation task, it can be automatically transformed into a semantic segmentation (only one mask for every class) or object detection (bounding boxes for every object) tasks. There are 1456 (20% of the total) unlabeled images (i.e. without annotations). There are 4 splits in the dataset: trainval (2913 images), train (1464 images), test (1456 images), and val (1449 images). The dataset was released in 2012 by the UK joint research group.

Here are the visualized examples for the classes:

The VOC data includes images obtained from the “flickr” website. Use of these images must respect the corresponding terms of use:

• "flickr" terms of use

For the purposes of the challenge, the identity of the images in the database, e.g. source and name of owner, has been obscured. Details of the contributor of each image can be found in the annotation to be included in the final release of the data, after completion of the challenge. Any queries about the use or ownership of the data should be addressed to the organizers.

⚠️ Warning The license for annotations is not clearly defined by the authors of the dataset.

Source

If you make use of the PASCAL VOC 2012 data, please cite the following reference:

@misc{pascal-voc-2012,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"
}

Source

Dataset PASCAL VOC 2012 can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='PASCAL VOC 2012', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here:

• Training/validation data
• Development kit code and documentation
• PDF documentation
• HTML documentation
• Guidelines used for annotating the database (VOC2011)
• Action guidelines used for annotating the action task images