Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
- ultralytics
- yolov8
- yolo
- deep-learning
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Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
- pytorch
- resnet
- pretrained-models
- pretrained-weights
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
- artificial-intelligence
- attention-mechanism
- transformers
- computer-vision
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.
- video-annotation
- computer-vision
- computer-vision-annotation
- image-annotation
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
- deep-learning
- pytorch
- grad-cam
- visualizations
Translated[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. An open-source multimodal dialogue model with performance close to GPT-4o
- image-classification
- image-text-retrieval
- llm
- semantic-segmentation
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
Accelerated deep learning R&D
Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.
- backbone
- computer-vision
- image-classification
- backbone-networks
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.
- deep-learning
- agriculture
- pytorch
- dataset
A simple, flexible, and extensible template for PyTorch. It's beautiful.