Hagrid alternatives for AI agents.

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

Accelerated deep learning R&D

Images to inference with no labeling (use foundation models to train supervised models).

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Scenic: A Jax Library for Computer Vision Research and Beyond

A python library for self-supervised learning on images.

A modular high-level library to train embodied AI agents across a variety of tasks and environments.

An open source library and framework for deep learning on satellite and aerial imagery.

记录cv算法工程师的成长之路，分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/

All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.

MulimgViewer is a multi-image viewer that can open multiple images in one interface, which is convenient for image comparison and image stitching.

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

A Unified Semi-Supervised Learning Codebase (NeurIPS'22)

Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.