OpenLabeling

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OpenLabeling is an open-source tool for labeling images and videos for computer vision applications. It supports multiple annotation formats like PASCAL VOC and YOLO darknet.

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At a glance

Pricing

free

Free tier

Yes

API

—

Skill level

Technical

About

What is OpenLabeling?

OpenLabeling is an open-source tool specifically designed for annotating images and videos, catering to the needs of computer vision applications. It offers support for various popular annotation formats, including PASCAL VOC and YOLO darknet, making it versatile for different project requirements. The tool's primary focus is to streamline and facilitate tasks related to object detection and image recognition. Users can efficiently label images in diverse formats, aiding in the creation of high-quality datasets for training machine learning models.

Best used for

Creating annotated datasets for training computer vision models, especially for object detection and image recognition.

Common actions

Label data

Annotate images

Prepare datasets

Train computer vision models

Object detection

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Capabilities

Key features

Image and video labeling
Open-source
PASCAL VOC support
YOLO darknet support
Object detection tasks

Target Audience

Machine Learning EngineersData ScientistsComputer Vision ResearchersAI Developers

Integrations

Not yet documented

Pricing & Plans

free

Free

FAQs

Does OpenLabeling support video annotation for object tracking over time?

Yes, OpenLabeling supports video annotation, allowing users to label objects across frames. While it primarily focuses on object detection in individual frames, its video capabilities facilitate creating datasets for object tracking tasks.

Can I import existing annotations from other tools into OpenLabeling?

OpenLabeling is designed to export in formats like PASCAL VOC and YOLO darknet. While direct import of arbitrary external formats might require conversion, its open-source nature allows for custom scripts to adapt existing annotations if they align with supported structures.

What are the hardware requirements for running OpenLabeling smoothly, especially with large datasets?

As a desktop application, OpenLabeling's performance depends on your local machine. For large image or video datasets, a system with a good CPU, ample RAM (16GB+ recommended), and potentially an SSD will provide the best experience for efficient labeling.

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