Command-line program to download videos from YouTube.com and other video sites

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Models and examples built with TensorFlow

Deep Learning for humans

scikit-learn: machine learning in Python

⏬ Dumb downloader that scrapes the web

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

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

The fundamental package for scientific computing with Python.

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

🍰 Desktop utility to download images/videos/music/text from various websites, and more.

Open standard for machine learning interoperability

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

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

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Parallel computing with task scheduling

Open deep learning compiler stack for cpu, gpu and specialized accelerators

Style transfer, deep learning, feature transform

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

Minimal PyTorch implementation of YOLOv3

🔥 2D and 3D Face alignment library build using pytorch

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also …

Official PyTorch implementation of StyleGAN3

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

Progressive Growing of GANs for Improved Quality, Stability, and Variation

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.