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LabelMe is a web-based tool to create and explore image databases for computer vision tasks. You can label objects, edit annotations, upload your own images and access public collections.
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.
May 9, 2016 · 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).
Oct 14, 2022 · LabelMe is an open-source Python tool for labeling image and video data for computer vision projects. Learn how to install, use, and export LabelMe, and explore its features and limitations.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation). - Releases · wkentaro/labelme.
Jul 20, 2023 · LabelMe is an open source image annotation tool, inspired by MIT's web annotation tool of the same name. LabelMe allows you to create annotations for object detection, classification, and segmentation computer vision datasets. You can draw annotations using polygon, rectangle, circle, line, and points.
