Ultralytics YOLO 🚀

We write your reusable computer vision tools. 💜

OpenMMLab Detection Toolbox and Benchmark

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Effortless data labeling with AI support from Segment Anything and other awesome models.

[ICLR 2026] RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning.

A simple, fully convolutional model for real-time instance segmentation.

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

🛰️ List of satellite image training datasets with annotations for computer vision and deep learning

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥

A Simple and Versatile Framework for Object Detection and Instance Recognition

pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.

Images to inference with no labeling (use foundation models to train supervised models).

Unofficial implemention of lanenet model for real time lane detection

Turn any computer or edge device into a command center for your computer vision projects.

[CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone

SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.