Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
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Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
We write your reusable computer vision tools. 💜
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
An open source implementation of CLIP.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Accelerated deep learning R&D
An open source library and framework for deep learning on satellite and aerial imagery.
Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
A simple, flexible, and extensible template for PyTorch. It's beautiful.
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources