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hub-er's Projects

algo icon algo

记录一些常见算法

bolt icon bolt

Binary Optimization and Layout Tool - A linux command-line utility used for optimizing performance of binaries

contrib icon contrib

[EOL] This is a place for various components in the Kubernetes ecosystem that aren't part of the Kubernetes core.

dbdev_autogen icon dbdev_autogen

An auto frame-generation tool for developing oracle interfaces

deepfacelab icon deepfacelab

DeepFaceLab is a tool that utilizes deep learning to recognize and swap faces in pictures and videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md).

distribuuuu icon distribuuuu

The pure and clear PyTorch Distributed Training Framework.

faiss icon faiss

A library for efficient similarity search and clustering of dense vectors.

greedysnake icon greedysnake

c++经典项目贪吃蛇游戏控制台版,详细注释

in-prestissimo icon in-prestissimo

A very fast neural network computing framework optimized for mobile platforms.QQ group: 676883532 【验证信息输:绝影】

ir-net icon ir-net

This project is the PyTorch implementation of our accepted CVPR 2020 paper : forward and backward information retention for accurate binary neural networks.

learnpaddle2 icon learnpaddle2

PaddlePaddle Fluid 版本系列教程,CSDN博客专栏:https://blog.csdn.net/qq_33200967/column/info/28685

mnn icon mnn

MNN is a lightweight deep neural network inference engine.

ncnn icon ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

netron icon netron

Visualizer for deep learning and machine learning models

openblas icon openblas

OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version.

pcn-facedetection-facealignment icon pcn-facedetection-facealignment

Progressive Calibration Networks (PCN) is an accurate rotation-invariant face detector running at real-time speed on CPU, published in CVPR 2018.

protobuf icon protobuf

Protocol Buffers - Google's data interchange format

qnnpack icon qnnpack

Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators

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