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We Found 5 domains on IP 126.96.36.199 listing below the same server this website
Labelme.com search for results as listed below with the link list and email address for this website
Welcome to LabelMe, the open annotation tool. 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.
Link: http://labelme.csail.mit.edu/Release3.0/ (Actived: Friday May 17, 2019)
Link: https://github.com/wkentaro/labelme (Actived: Wednesday May 15, 2019)
LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) which 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. As of October 31, 2010, LabelMe has 187,240 images, 62,197 annotated images, and 658,992
Link: https://en.wikipedia.org/wiki/LabelMe (Actived: Monday May 13, 2019)
labelme # just open gui # tutorial (single image example) cd examples/tutorial labelme apc2016_obj3.jpg # specify image file labelme apc2016_obj3.jpg -O apc2016_obj3.json # close window after the save labelme apc2016_obj3.jpg --nodata # not include image data but relative image path in JSON file labelme apc2016_obj3.jpg \--labels highland_6539
Link: https://pypi.org/project/labelme/ (Actived: Friday May 17, 2019)
Link: https://github.com/CSAILVision/LabelMeAnnotationTool (Actived: Monday May 13, 2019)
Link: https://label-me.com/ (Actived: Friday May 17, 2019)
The LabelMe Matlab toolbox is designed to allow you to download and interact with the images and annotations in the LabelMe database. The toolbox contains functions for plotting and querying the annotations, computing statistics, dealing with synonyms, etc. This page gives a step-by-step overview of the main toolbox functionalities.
Link: http://labelme2.csail.mit.edu/Release3.0/browserTools/php/matlab_toolbox.php (Actived: Saturday May 4, 2019)
labelme.org, a crowdsourceing platform. Toggle navigation Label Me. Login; A Crowdsourcing platform for labeling fundus images help improving AI algorithm by labeling retinal diseases. Be collaborative join the team and build up a knowledge base. Image Set. More than 200,000 full-color fundus photos included.
Link: http://labelme.org/ (Actived: Friday May 17, 2019)
Send email to [email protected] if you have suggestions, find bugs or there are new features that you would like to see in the tool. Credits. The LabelMe app has been developed by Dolores Blanco, Aina Torralba, David Way, Josep Marc Ming0t and Antonio Torralba. (c) MIT, Computer Science and Artificial Intelligence Laboratory.
Link: http://labelme2.csail.mit.edu/Release3.0/browserTools/php/iPhoneHelp.php (Actived: Tuesday May 7, 2019)
Link: http://www.jinglingbiaozhu.com/ (Actived: Saturday May 18, 2019)
Publications Train in Spain and test in the rest of the world. Try to recognize and segment as many object categories as you can. Training images correspond to outdoor pictures taken in different cities of Spain.
Link: http://labelme2.csail.mit.edu/Release3.0/browserTools/php/publications.php (Actived: Thursday May 16, 2019)