LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) that provides a dataset of digital images with annotations.
The motivation behind creating LabelMe comes from the history of publicly available data for computer vision researchers.
The LabelMe annotation tool provides a means for users to contribute to the project.
To access the tool, users must have a compatible web browser with JavaScript support.
When the tool is loaded, it chooses a random image from the LabelMe dataset and displays it on the screen.
Once the polygon is closed, a bubble pops up on the screen which allows the user to enter a label for the object.
As soon as changes are made to the image by the user, they are saved and openly available for anyone to download from the LabelMe dataset.
This is due to the images being primarily taken by humans who tend to focus the camera on interesting objects in a scene.
Some problems that arise are: The creators of LabelMe decided to leave these decisions up to the annotator.
Ideally, when using the data, the object class dog at the abstract level should incorporate all of these text labels.
Since research is often done in Matlab, this allows the integration of the dataset with existing tools in computer vision.