Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
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Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
We write your reusable computer vision tools. 💜
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
OpenMMLab Detection Toolbox and Benchmark
deep learning for image processing including classification and object-detection etc.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
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.
Image augmentation for machine learning experiments.
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型
A unified framework for machine learning with time series
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
A simple, fully convolutional model for real-time instance segmentation.
Accelerated deep learning R&D
A Simple and Versatile Framework for Object Detection and Instance Recognition
An open source library and framework for deep learning on satellite and aerial imagery.
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)