Labelme

What is LabelMe?

LabelMe is a powerful and trusted tool for creating high-quality vision datasets, widely recognized as the industry standard among over 15,000 builders. This offline image annotation^[1] application allows users to efficiently annotate images using various shapes such as polygons^[2], bounding boxes^[3], and segmentation^[4]. With a one-time purchase model and no subscription fees, LabelMe offers an accessible solution for developers and researchers looking to build training datasets privately and quickly, without the need for cloud uploads.

How to use LabelMe?

1. Download and install the LabelMe annotation app from the official website.
2. Launch the app and open an image you want to annotate.
3. Use the available tools to create annotations such as polygons or rectangles by clicking and dragging on the image.
4. Add any necessary attributes or labels to your annotations.
5. Once your annotations are complete, validate them and export the dataset using the Toolkit.

What are the main features of LabelMe?

• Offline Annotation: LabelMe operates completely offline, ensuring data privacy and security.
• Versatile Annotation Tools: Users can annotate images with various shapes including polygons, rectangles, and circles.
• AI-Assisted Annotation: The tool provides real-time feedback and auto-annotation features using AI models, enhancing efficiency.
• Rich Attributes: Users can add detailed flags and texts to their annotations for better dataset management.
• Automation Toolkit: Command-line tools facilitate batch processing and integration with existing workflows.

Who is LabelMe for?

LabelMe is designed for developers, researchers, and data scientists who need to create high-quality datasets for computer vision tasks. It is particularly beneficial for those working in fields such as robotics, autonomous vehicles, agriculture, and medical imaging. The tool is suitable for both individual users and teams looking for a reliable solution to annotate images privately and efficiently.

What are the use cases of LabelMe?

1. Self-Driving Cars: Annotate images to train models for detecting vehicles, pedestrians, and road signs.
2. Medical Imaging: Create datasets for training AI models to identify abnormalities in medical scans.
3. Retail and Inventory Management: Annotate product images to enhance object recognition in inventory systems.