CVHub520/X-AnyLabeling

What it solves

X-AnyLabeling is a unified cross-platform desktop application designed to simplify and accelerate the process of annotating text, image, video, and multimodal data. It reduces the manual effort required for data labeling by integrating AI-assisted tools and automated labeling workflows.

How it works

The tool provides a comprehensive suite of built-in annotation tools (such as polygons, rectangles, and masks) and integrates a wide range of state-of-the-art deep learning models for automated labeling and batch prediction. It supports both local inference using engines like ONNX Runtime and TensorRT, or remote inference via the X-AnyLabeling-Server backend. Users can import and export data in various industry-standard formats like COCO, VOC, YOLO, and ShareGPT.

Who it’s for

Data scientists, ML engineers, and researchers who need to create high-quality labeled datasets for computer vision, OCR, and multimodal AI models.

Highlights

• Unified Platform: Supports image classification, object detection, instance segmentation, pose estimation, and more across text, image, and video.
• Model Library: Integrates a vast array of models including YOLO series, SAM (Segment Anything Model), and various Vision Language Models (VLMs) like Qwen3-VL and Gemini.
• Flexible Inference: Offers both local and remote inference capabilities to leverage custom compute resources.
• Cross-Platform: Runs on Windows, Linux, and macOS with multi-language interface support.
• Extensive Format Support: Compatible with numerous import/export formats including COCO, VOC, and YOLO.