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ai_projects

从2019年4月起完成的各种人工智能相关工程

alphazero_gomoku

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

anime4k

A High-Quality Real Time Upscaler for Anime Video

centernet

Object detection, 3D detection, and pose estimation using center point detection:

cnngraph

A tool that automatically extracts network structures from Tensorflow model files

darknet

Convolutional Neural Networks

deepcreampy

Decensoring Hentai with Deep Neural Networks

deepshift

Implementation of "DeepShift: Towards Multiplication-Less Neural Networks" https://arxiv.org/abs/1905.13298

deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

elf

ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

g.pt

Official PyTorch Implementation of Learning to Learn with Generative Models of Neural Network Checkpoints

ghostnet

[CVPR2020] Surpassing MobileNetV3: "GhostNet: More Features from Cheap Operations"

grad-cam-keras

Grad-CAM implementation in Keras

graph-neural-networks

hcnn

Hexagonal CNN

heatmap

Python module to create heatmaps

keras-centernet

A Keras implementation of CenterNet with pre-trained model (unofficial)

keras-tuner

Hyperparameter tuning for humans

keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

kuzushi

leela-zero-pytorch

A simple PyTorch + PyTorch Lightning training pipeline for Leela Zero

maskrcnn-benchmark

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

ndl

numpy-ml

Machine learning, in numpy

pysc2

StarCraft II Learning Environment

pysc2-examples

StarCraft II - pysc2 Deep Reinforcement Learning Examples

pythonsatsolver

A SAT solver written in Python 3.2 using three different algorithms; DPLL, Hill Climbing, and Genetic

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration