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py labelme

Broad/Unclear specialization

Quick facts

Company
py labelme
Service type
Data annotation / AI training data
Specialties
Image, Text
Hiring status
Both: hires workers and takes vendor projects
Website
labelme.csail.mit.edu
Careers
Unavailable
Profile last verified
2026-01-29

Application process overview

LabelMe (labelme.csail.mit.edu) is an open-source image annotation tool and dataset originally developed at MIT CSAIL, with a related Python desktop tool commonly installed as `pip install labelme`. It is research software for creating polygon, bounding-box, and segmentation annotations, not a company or paid work platform.

Key findings

Application Process: No application; anyone can use the online LabelMe tool at the MIT site or install the open-source Python desktop app from GitHub.<br><br>Assessments: None; it is a tool, not a workforce.<br><br>Job Types / Expertise: Users self-serve to annotate their own images for research, teaching, or ML projects; also used to build and extend the public LabelMe dataset.<br><br>Compensation: Unpaid; the original MIT LabelMe was designed as a volunteer/research annotation effort, and contributions to the dataset are not compensated.<br><br>Flexibility: Fully self-paced, offline or online, with no commitments.<br><br>Challenges / Concerns: People searching for paid annotation work sometimes confuse LabelMe with a gig platform; there is no job system, login-based earnings, or support infrastructure for workers.<br><br>Legitimacy: Legitimate academic project, widely cited in computer vision literature (Russell et al., IJCV 2008), with the Python tool actively maintained on GitHub under an MIT-compatible license.

Conclusion

LabelMe is a respected open-source tool and dataset from MIT CSAIL, not a company offering paid annotation work. It is highly useful for researchers and developers who need to label their own image data, but it does not provide jobs, tasks, or income. Anyone encountering it in a list of 'annotation companies' should understand it is tooling rather than a workforce. Its legitimacy as academic software is strong; its relevance to paid work is zero.