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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.
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.
Jun 13, 2024 · 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).
Use LabelMe, the open annotation tool, to label images online and share them with the research community.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation). - Releases · labelmeai/labelme.
The goal of LabelMe is to provide an online annotation tool to build a large database of annotated images by collecting contributions from many people. You can contribute to the database by visiting the annotation tool.
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 dataset is dynamic, free to use, and open to public contribution. The most applicable use of LabelMe is in computer vision research.
