he Pascal VOC (Visual Object Classes) format is one of the earlier established benchmarks for object classification and detection, which provides a standardized image data set for object class recognition.

The export data format is XML-based and has been widely adopted in computer vision tasks.

For more information, see:

Pascal VOC export

For export of images:

  • Supported annotations: Bounding Boxes (detection), Tags (classification), Polygons (segmentation)
  • Attributes:
    • occluded as both UI option and a separate attribute.
    • truncated and difficult must be defined for labels as checkbox.
    • Arbitrary attributes in the attributes section of XML files.
  • Tracks: Not supported.

The downloaded file is a .zip archive with the following structure:

taskname.zip/
├── JPEGImages/
│   ├── <image_name1>.jpg
│   ├── <image_name2>.jpg
│   └── <image_nameN>.jpg
├── Annotations/
│   ├── <image_name1>.xml
│   ├── <image_name2>.xml
│   └── <image_nameN>.xml
├── ImageSets/
│   └── Main/
│       └── default.txt
└── labelmap.txt

# labelmap.txt
# label : color_rgb : 'body' parts : actions
background:::
aeroplane:::
bicycle:::
bird:::

Pascal VOC import

Supported attributes: action attributes (import only, should be defined as checkbox -es)

Uploaded file: a zip archive of the structure declared above or the following:

taskname.zip/
├── <image_name1>.xml
├── <image_name2>.xml
└── <image_nameN>.xml

It must be possible for CVAT to match the frame name and file name from annotation .xml file (the filename tag, e. g. <filename>2008_004457.jpg</filename> ).

There are 2 options:

  1. full match between frame name and file name from annotation .xml (in cases when task was created from images or image archive).

  2. match by frame number. File name should be <number>.jpg or frame_000000.jpg. It should be used when task was created from video.

How to create a task from Pascal VOC dataset

  1. Download the Pascal Voc dataset (Can be downloaded from the PASCAL VOC website)

  2. Create a CVAT task with the following labels:

    aeroplane bicycle bird boat bottle bus car cat chair cow diningtable
    dog horse motorbike person pottedplant sheep sofa train tvmonitor
    

    You can add ~checkbox=difficult:false ~checkbox=truncated:false attributes for each label if you want to use them.

    Select interesting image files (See Creating an annotation task guide for details)

  3. zip the corresponding annotation files

  4. click Upload annotation button, choose Pascal VOC ZIP 1.1

    and select the zip file with annotations from previous step. It may take some time.