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The goal of LabelMe is to provide an online annotation tool to build image databases for computer vision research. You can contribute to the database by visiting the annotation tool. Label objects in the images. Edit your annotations. Upload your own pictures and explore the public collections. Log In. Username Password Forgot your password?
Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu. It is written in Python and uses Qt for its graphical interface. VOC dataset example of instance segmentation. Other examples (semantic segmentation, bbox detection, and classification). Various primitives (polygon, rectangle, circle, line, and point). Features.
LabelMe is an online annotation tool to build a large database of annotated images by collecting contributions from many people.
Labeling instructions. When you enter the tool, an image from the database will be randomly selected and shown. You can help by annotating as many objects as you can. Note that previously labeled objects may appear on the image. Please do not label previously labeled objects.
🚀 Features. Support multiple edit of annotations #1455 (Thanks @Daasein) Show xy coordinate in the status bar #1456. Enhancement. Use with statement to open file to make code more Pythonic #1370 (Thanks @anonymousdouble) Save mask as uint8 for better compatibility with other tools #1452.
By signing in you can keep track of your annotations!If you download the dataset, you may wish to work with only those labels that you add. With the LabelMe Matlab toolbox, you may query annotations based on your submitted username.
LabelMe allows you to create, upload and annotate image databases for research purposes. Learn how to use the tool, organize images into collections, and share your annotations with the world.