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Cao E's Projects

keras-yolo2 icon keras-yolo2

Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

lightseq icon lightseq

LightSeq: A High Performance Library for Sequence Processing and Generation

maddpg icon maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

mindspore icon mindspore

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

mtl icon mtl

MTL 多端开发解决方案

multimodal icon multimodal

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

onednn icon onednn

oneAPI Deep Neural Network Library (oneDNN)

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-gan icon pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

pytorch-unet icon pytorch-unet

Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation

restormer icon restormer

[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.

riscv_cpu icon riscv_cpu

A FPGA supported RISC-V CPU with 5-stage pipeline implemented in Verilog HDL

shinydata icon shinydata

A GUI for interactive data analysis, visualization and presentation

training icon training

Training material to get started with the HEADS technologies

transformers icon transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

vision icon vision

Datasets, Transforms and Models specific to Computer Vision

xtext icon xtext

Eclipse Xtext™ is a language development framework

zhihu icon zhihu

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

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