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PyTorch implementation of VisionHOPE, a visual backbone based on self-referential nested learning (SRNL).

AI-assisted RAW photo developer: GPT vision advisor proposes an EditRecipe, a deterministic Rust engine renders it — Lightroom-compatible XMP sidecars, 24 RAW formats + baked images, measured (not guessed) Lightroom mask geometry, local GUI/web UI, AI denoise & segmentation…

Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use.

X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

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.

[2026-03-10] The Canopy Height Maps v2 (CHMv2) model and inference code are now available (more details on downloading the model weights and using the code here). The model weights are also available in Hugging Face Hub and supported by the Hugging Face Transformers library.

CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs.

The largest collection of PyTorch image encoders / backbones.

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

txt inference code, following DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment.

Ultralytics YOLOv5 🚀 is a fast, accurate, and easy-to-use computer vision model developed by Ultralytics. Based on the PyTorch framework, YOLOv5 is renowned for its speed, accuracy, and simplicity.

Note 1: For Windows, please install torch and torchvision first by following the official instructions here On the pytorch website, be sure to select the right CUDA version you have. If you intend to run on CPU mode only, select CUDA = None.

These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards.

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

The open-source tool for building high-quality datasets and computer vision models

deep learning for image processing including classification and object-detection etc.

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes.

The models were pre-trained on the ImageNet and ImageNet-21k datasets. We provide the code for fine-tuning the released models in JAX/Flax.

This project is about explaining what machine learning classifiers (or models) are doing.

This repository contains demos I made with the Transformers library by HuggingFace.

Implementation of Vision Transformer , a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch. Significance is further explained in Yannic Kilcher's video.

The following is the corresponding torchvision versions and supported Python versions.

深度学习入门教程, 优秀文章, Deep Learning Tutorial

State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!

This is a set of scripts that allows for an automatic collection of tens of thousands of images for the following (loosely defined) categories to be later used for training an image classifier: - porn - pornography images - hentai - hentai images, but also includes pornographic…

cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

Techniques for deep learning with satellite & aerial imagery