Open source. Open possibilities.

A comprehensive toolkit for computer vision that provides model-agnostic building blocks for data loading, visualization, and dataset management.

X-AnyLabeling is a cross-platform desktop application for AI-assisted annotation of image, video, text, and multimodal data, with many built-in deep learning models, diverse labeling tools, and multi-format import/export.

Ultralytics provides a suite of state-of-the-art YOLO models for computer vision tasks including object detection, segmentation, and classification.

RF-DETR is a real-time transformer model architecture from Roboflow for object detection, instance segmentation, and keypoint detection, built on a DINOv2 backbone and designed for fine-tuning.

YOLOv5 is a fast, accurate computer vision framework in PyTorch for object detection, instance segmentation, and image classification. It supports training on custom datasets, inference from various sources, and exporting models to formats like ONNX, TensorRT, and CoreML.