Open source. Open possibilities.

FiftyOne is an open-source tool for building high-quality datasets and computer vision models. It enables users to visualize, label, evaluate, and curate visual AI data.

A growing collection of 61 computer vision tutorials covering state-of-the-art models like YOLO11, SAM 3, RF-DETR, and Qwen3-VL for object detection, segmentation, OCR, and more.

timm is a large collection of PyTorch image models, layers, optimizers, schedulers, data loaders and training/eval scripts, offering many pretrained backbones such as ResNet, EfficientNet, ViT, ConvNeXt and Swin.

Label Studio is an open-source, multi-type data labeling tool supporting audio, text, images, video, and time series with a simple UI and export to various model formats.

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.

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.