Image Classification GitHub Repositories (2026) · Open Source Tools

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

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.

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

Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.

Refine high-quality datasets and visual AI models

Label Studio is a multi-type data labeling and annotation tool with standardized output format

Local-first AI photo culling for professional photographers — 6-axis rubric, XMP/IPTC export, Lightroom & Capture One ready.

Teach a local AI what your camera sees and turn it into Home Assistant sensors — garage door open/closed, gate shut, car parked. 100% local, any CPU.

Image augmentation for computer vision. AGPL-3.0-only or commercial licensing.

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).

High-performance Ultralytics YOLO inference in Rust with ONNX Runtime, GPU backends, CLI, and WebGPU/WASM.