A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

A Python Perceptual Image Hashing Module

CnOCR: Awesome Chinese/English OCR Python toolkits based on PyTorch. It comes with 20+ well-trained models for different application scenarios and can be used directly after installation. 【基于 PyTor…

「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

✂️ Automated high-quality background removal framework for an image using neural networks. ✂️

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

Python version of algorithm-pattern

This is the English version of the Image processing 100 questions.

Rendered math (MathJax) with Slack's desktop client

Code for CIKM2020 "S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization"

Object detection achieving 44.3 mAP / 45 fps on COCO dataset

The official repo is https://github.com/dmlc/dgl . THIS IS A FORK.

Implementation of Stochastic Beam Search using Fairseq

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

Retinaface pytorch face-pose-detect face-key-point-detect

Deep Learning Tutorial notes and code. See the wiki for more info.

Real-time VIBE: Frame by Frame Inference of VIBE (Video Inference for Human Body Pose and Shape Estimation)

A JupyterLab extension for displaying dashboards of GPU usage.

PyTorch implementation for the Neural Logic Machines (NLM).

DataFountain第五届达观杯第4名方案

Deep Structure Learning for Fraud Detection (ICDM 2018)

FraudNE: a Joint Embedding Approach for Fraud Detection (IJCNN 2018)

Diffusion Convolutional Recurrent Neural Network Implementation in PyTorch

Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Model interpretability and understanding for PyTorch

A benchmark for offline reinforcement learning.