image-classification

27 projetos partilham este topic do GitHub

image-classification — ultralytics ★59.6kimage-classificationvit-pytorch — ★25.4kInternVL — ★10.1khave-fun-with-machine-learning — ★5.1kdarts — ★4khub — ★3.5kcatalyst — ★3.4kAlphaTree-graphic-deep-neural-network — ★3kdeepdetect — ★2.6kbootcamp — ★2.4kAwesome-Backbones — ★2kTensorRT-YOLO — ★1.9kpytorch-toolbelt — ★1.6kLibFewShot — ★1.1kAwesome-CV-MasterHub — ★960YoloDotNet — ★796Image-Augmentation — ★700ISP-Guide — ★685bottleneck-transformer-pytorch — ★678DynamicViT — ★668BiFormer — ★581GFNet — ★511computer-vision — ★508Alturos.Yolo — ★431mixstyle-release — ★333pytorch-vit — ★309transformer-in-transformer — ★306vit-pytorch★ 25.4kInternVL★ 10.1khave-fun-with-machine-le…★ 5.1kdarts★ 4khub★ 3.5kcatalyst★ 3.4kAlphaTree-graphic-deep-n…★ 3kdeepdetect★ 2.6kbootcamp★ 2.4kAwesome-Backbones★ 2kTensorRT-YOLO★ 1.9kpytorch-toolbelt★ 1.6kLibFewShot★ 1.1kAwesome-CV-MasterHub★ 960YoloDotNet★ 796Image-Augmentation★ 700ISP-Guide★ 685bottleneck-transformer-p…★ 678DynamicViT★ 668BiFormer★ 581GFNet★ 511computer-vision★ 508Alturos.Yolo★ 431mixstyle-release★ 333pytorch-vit★ 309transformer-in-transform…★ 306

Linhas conectam membros que estão mensuravelmente relacionados entre si. O tamanho do ponto reflete estrelas.

🧬 Membros
ultralytics
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image…
★ 59.6k
vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a…
★ 25.4k
InternVL
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. …
★ 10.1k
have-fun-with-machine-learning
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
★ 5.1k
darts
Differentiable architecture search for convolutional and recurrent networks
★ 4k
hub
A library for transfer learning by reusing parts of TensorFlow models.
★ 3.5k
catalyst
Accelerated deep learning R&D
★ 3.4k
AlphaTree-graphic-deep-neural-network
★ 3k
deepdetect
Deep Learning Server and CLI for Torch and TensorRT
★ 2.6k
bootcamp
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video…
★ 2.4k
Awesome-Backbones
Integrate deep learning models for image classification | Backbone learning/comparison/magic modification…
★ 2k
TensorRT-YOLO
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
★ 1.9k
pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
★ 1.6k
LibFewShot
[TPAMI 2023] LibFewShot: A Comprehensive Library for Few-shot Learning.
★ 1.1k
Awesome-CV-MasterHub
:fire: :fire: :fire: A paper list of some recent Computer Vision(CV) works
★ 960
YoloDotNet
YoloDotNet - A C# .NET 8.0 project for Classification, Object Detection, OBB Detection, Segmentation and Pose…
★ 796
Image-Augmentation
Image augmentation for object detection, segmentation and classification
★ 700
ISP-Guide
Image Signal Processing (ISP) Guide. Learn all about the process of converting an image/video into digital…
★ 685
bottleneck-transformer-pytorch
Implementation of Bottleneck Transformer in Pytorch
★ 678
DynamicViT
[NeurIPS 2021] [T-PAMI] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
★ 668
BiFormer
[CVPR 2023] Official code release of our paper "BiFormer: Vision Transformer with Bi-Level Routing Attention"
★ 581
GFNet
[NeurIPS 2021] [T-PAMI] Global Filter Networks for Image Classification
★ 511
computer-vision
Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual…
★ 508
Alturos.Yolo
C# Yolo Darknet Wrapper (real-time object detection)
★ 431
mixstyle-release
Domain Generalization with MixStyle (ICLR'21)
★ 333
pytorch-vit
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
★ 309
transformer-in-transformer
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for…
★ 306
🔗 Familias relacionadas

Medido a partir dos tópicos do GitHub compartilhados por ambos os projetos, ponderado pela raridade de cada tópico.