LabelME
Web-based tool for labeling image datasets
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
UnverifiedOverview
What is LabelME?
LabelME is a web-based tool that allows users to annotate images with object labels and segmentation masks, facilitating the creation of labeled datasets for machine learning tasks.
Key differentiator
“LabelME stands out as a flexible, open-source tool specifically designed for creating labeled datasets with object labels and segmentation masks, making it ideal for research and educational projects.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
Primary documentation is limited to basic usage examples; extensive troubleshooting information is scarce.
Web-based interface can become unresponsive or slow when handling a high volume of images or annotations.
Primary support and development focus is on Python, with limited official SDKs for other languages.
Fit analysis
Who is it for?
✓ Best for
Research teams needing a flexible tool to annotate image datasets with object labels and segmentation masks
Educational projects that require hands-on experience in creating labeled datasets
✕ Not a fit for
Teams requiring real-time annotation capabilities or integration into existing cloud services
Projects that need high-throughput data labeling for large-scale production environments
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with LabelME
Step-by-step setup guide with code examples and common gotchas.