absorbguo Goto Github PK

gluon-tutorials-zh

通过MXNet/Gluon来动手学习深度学习

go

The Go programming language

google-research

Google AI Research

goturn

Source code for paper: Learning to Track at 100 FPS with Deep Regression Networks, Held, et al. ECCV 2016

gpcyclegan

Akshay Rangesh, Bowen Zhang and Mohan Trivedi, "Driver Gaze Estimation in the Real World: Overcoming the Eyeglass Challenge," IEEE Intelligent Vehicles Symposium (IV), 2020.

gpustat

📊 A simple command-line utility for querying and monitoring GPU status

halide

a language for fast, portable data-parallel computation

handong1587.github.io

hello-world

just a test repository

hfsoftmax

Accelerated Training for Massive Classification via Dynamic Class Selection

horizonface

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and MXNet.

how-to-optimize-gemm

icnet

ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

icnet-pytorch

ICNet implemented by pytorch, for real-time semantic segmentation on high-resolution images, mIOU=71.0 on cityscapes, single inference time is 19ms, FPS is 52.6.

imagededup

😎 Finding duplicate images made easy!

insightface

Face Recognition Project on MXNet

ipython

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

itchat

A complete and graceful API for Wechat. 微信个人号接口、微信机器人及命令行微信，三十行即可自定义个人号机器人。

kcfpy

Python implementation of KCF tracking algorithm

lab

[CVPR 2018] Look at Boundary: A Boundary-Aware Face Alignment Algorithm

labelme

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

learning-dl

Learning Deep Learning

loss-landscape

Code for visualizing the loss landscape of neural nets

market-1501_attribute

27 hand-annotated attributes of Market-1501

matmul

Benchmarking matrix multiplication implementations

mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

mlss2018-madrid-gan

MLSS 2018 Madrid lecture materials on Generative Adversarial Networks (GANs)

mmdnn

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, PyTorch Onnx and CoreML.

mobile-deep-learning

This research aims at simply deploying CNN(Convolutional Neural Network) on mobile devices, with low complexity and high speed.