Pascal VOC Dataset

The Pascal VOC (PASCAL Visual Object Classes) data is a well known set of standardised images for object class recognition.

Getting the Pascal VOC data

The Pascal VOC dataset is not included in the CNTK distribution but can be easily downloaded by running the following Python command:

python install_pascalvoc.py

This will download roughly 3.15GB of data and unpack it into the folder structure that is assumed in the object recognition tutorial

Alternative: download data manually

You need the 2007 (trainval and test) and 2012 (trainval) data as well as the precomputed ROIs used in the original Fast R-CNN paper. For the object recognition tutorial you need to follow the folder structure described below.

• Download and unpack the 2012 trainval data to DataSets/Pascal/VOCdevkit
  • Website: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
  • Devkit: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
• Download and unpack the 2007 trainval data to DataSets/Pascal/VOCdevkit
  • Website: http://host.robots.ox.ac.uk/pascal/VOC/voc2007/
  • Devkit: http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
• Download and unpack the 2007 test data into the same folder DataSets/Pascal/VOCdevkit
  • http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
• Download and unpack the precomputed ROIs to DataSets/Pascal/selective_search_data
  • http://www.cs.berkeley.edu/~rbg/fast-rcnn-data/selective_search_data.tgz

The VOCdevkit/VOC2007 folder should contain at least the following (similar for 2012):

VOCdevkit/VOC2007
VOCdevkit/VOC2007/Annotations
VOCdevkit/VOC2007/ImageSets
VOCdevkit/VOC2007/JPEGImages

Performance

If you are curious about how well computers can perform on Pascal VOC today, the official leaderboards are maintained at http://host.robots.ox.ac.uk:8080/leaderboard/main_bootstrap.php