Tensors and Dynamic neural networks in Python with strong GPU acceleration

Models and examples built with TensorFlow

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

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

Let us control diffusion models!

PyTorch Tutorial for Deep Learning Researchers

OpenMMLab Detection Toolbox and Benchmark

Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Image-to-Image Translation in PyTorch

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

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

Graph Neural Network Library for PyTorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

PyTorch implementations of Generative Adversarial Networks.

Datasets, Transforms and Models specific to Computer Vision

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

Image augmentation for machine learning experiments.

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

End-to-End Object Detection with Transformers

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Mamba SSM architecture

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…