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XImage

The eXtended image (Ximage) is a specification format that allows to embed complex metadata into image files like JPEGs or PNGs. It's based on the XMP ISO standard, an evolution of Exif.

The basic idea is to join the informations coming from the acquisition process and from the hand-made labeling (or from an AI classification) with the actual pixel data, in the same file, avoiding the use of sidecar files.

XImage use its own namespace (http://bioretics.com/aliquis) to define the schema of the metadata, mainly composed of:

  • Acquisition: a set of properties related to the acquision process. E.g: date, progressive shot id, dataset name, ...
  • Setup: a set of properties related to the acquisition setup. E.g: camera parameters, lights configuration, ...
  • Classes: an array of description-color pairs, describing what kind objects are used in the annotations and how they must be displayed.
  • Items: a set of objects present in the scene, identified by an UUID and represented by a hierarchy of blobs, that are areas of pixels belonging to a certain class.

The data are accessed through a single Python script ximage.py, which implements both the library and the main manipulation tool.

Functionalities

extract and inject

extract reads the XML of a Ximage and save it to a file. injects performs the opposite operation, reading an XML file and embedding its content into an existing image. This last operation is tipically useful when preparing a large set of images with the same base metadata, e.g. to inject acquisition, setup and classes properties into a set of images belonging to the same acquisition.

export and import

These commands handle the conversion of Ximage's items to and from an index mask (a grayscale image where each gray level corresponds to a class identifier).

With export it's possible to generate an index mask from a Ximage, whereas import searches for contours in an index mask and save them as items and blobs into a Ximage. These tools are useful when there is the need to convert an old dataset of image/index mask pairs to the Ximage format or, conversely, to create sibling index masks for tools that don't support the Ximage format.

update, uuid and view

update command inject new metadata in an image that is already a Ximage (by default, it will not overwrite or delete any current information). uuid is useful to get or set all items' UUID of a Ximage; view display items and blobs in a graphical interface, by drawing contours of blobs whose colors are defined by the respective class.

index and query

With these tools it's possibile to manage a large database of Ximages.

index command reads all images inside a folder and for each Ximage it saves metadata into a sqlite database, essentially indexing the whole folder, while query allows to search in the metadata database, and print the paths of Ximages that match the required features.

Example of database creation and querying

Suppose we have a folder ~/imgs of annotated Ximages of cats and dogs. We can index the folder and create a database with:

  cd ~/imgs
  ximage.py index .

Then we can search for images that contains a cat with:

  ximage.py query 'count(item.cat) > 0'

This will result in a list of all images paths that contains at least a cat in their annotation. Let's say we want images were there are both cats and dogs:

  ximage.py query 'count(item.cat) > 0 and count(item.dog) > 0'

If we want images containing at least 2 dogs:

  ximage.py query 'count(item.dog) >= 2'

The list of paths can than be used as an input for other programs, for example to build a dataset of relevant images.

Requirements

The tool is based on OpenCV (>=3) and python-xmp-toolkit (which in turn require the Exempi library). It works with both Python 2 and Python 3.

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Embed vision metadata into image files

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