Using pytorch to implement unet network for liver image segmentation.

Overview
> README.md git init git add README.md git commit -m "first commit" git branch -M main git remote add origin [email protected]:Z-XQ/unet_pytorch.git git push -u origin main …or push an existing repository from the command line git remote add origin [email protected]:Z-XQ/unet_pytorch.git git branch -M main git push -u origin main ">
…or create a new repository on the command line
echo "# unet_pytorch" >> README.md
git init
git add README.md
git commit -m "first commit"
git branch -M main
git remote add origin [email protected]:Z-XQ/unet_pytorch.git
git push -u origin main

…or push an existing repository from the command line
git remote add origin [email protected]:Z-XQ/unet_pytorch.git
git branch -M main
git push -u origin main

windows下同时使用gitlab和github

# 生成gitlab密钥
ssh-keygen -t rsa -C "[email protected]"
# 然后把生成的id_rsa.pub里面的内容复制到gitlab里面

# 准备github的ssh密钥
ssh-keygen -t rsa -C "[email protected]"-f id_rsa_github
# 然后把生成的id_rsa_github.pub里面的内容复制到github里面

# 也可以直接复制密钥id_rsa文件再命名为config
# 修改config内容:
#gitlab
Host gitlab
HostName gitlab.com
PreferredAuthentications publickey
IdentityFile C:\Users\Administrator\.ssh\id_rsa

#github
Host github
HostName github.com
PreferredAuthentications publickey
IdentityFile C:\Users\Administrator\.ssh\id_rsa_hub
Owner
zxq
Graduate student of Jiangxi University of Finance and Economics
zxq
A super lightweight Lagrangian model for calculating millions of trajectories using ERA5 data

Easy-ERA5-Trck Easy-ERA5-Trck Galleries Install Usage Repository Structure Module Files Version iteration Easy-ERA5-Trck is a super lightweight Lagran

Zhenning Li 26 Nov 19, 2022
A scikit-learn-compatible module for estimating prediction intervals.

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

SimAI 584 Dec 27, 2022
Automatic library of congress classification, using word embeddings from book titles and synopses.

Automatic Library of Congress Classification The Library of Congress Classification (LCC) is a comprehensive classification system that was first deve

Ahmad Pourihosseini 3 Oct 01, 2022
Learning Temporal Consistency for Low Light Video Enhancement from Single Images (CVPR2021)

StableLLVE This is a Pytorch implementation of "Learning Temporal Consistency for Low Light Video Enhancement from Single Images" in CVPR 2021, by Fan

99 Dec 19, 2022
A lossless neural compression framework built on top of JAX.

Kompressor Branch CI Coverage main (active) main development A neural compression framework built on top of JAX. Install setup.py assumes a compatible

Rosalind Franklin Institute 2 Mar 14, 2022
Neural network for digit classification powered by cuda

cuda_nn_mnist Neural network library for digit classification powered by cuda Resources The library was built to work with MNIST dataset. python-mnist

Nikita Ardashev 1 Dec 20, 2021
Equivariant Imaging: Learning Beyond the Range Space

[Project] Equivariant Imaging: Learning Beyond the Range Space Project about the

Georges Le Bellier 3 Feb 06, 2022
use machine learning to recognize gesture on raspberrypi

Raspberrypi_Gesture-Recognition use machine learning to recognize gesture on raspberrypi 說明 利用 tensorflow lite 訓練手部辨識模型 分辨 "剪刀"、"石頭"、"布" 之手勢 再將訓練模型匯入

1 Dec 10, 2021
Implementation of Neonatal Seizure Detection using EEG signals for deploying on edge devices including Raspberry Pi.

NeonatalSeizureDetection Description Link: https://arxiv.org/abs/2111.15569 Citation: @misc{nagarajan2021scalable, title={Scalable Machine Learn

Vishal Nagarajan 11 Nov 08, 2022
RID-Noise: Towards Robust Inverse Design under Noisy Environments

This is code of RID-Noise. Reproduce RID-Noise Results Toy tasks Please refer to the notebook ridnoise.ipynb to view experiments on three toy tasks. B

Thyrix 2 Nov 23, 2022
Optimizing Deeper Transformers on Small Datasets

DT-Fixup Optimizing Deeper Transformers on Small Datasets Paper published in ACL 2021: arXiv Detailed instructions to replicate our results in the pap

16 Nov 14, 2022
Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset

SW-CV-ModelZoo Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset Framework: TF/Keras 2.7 Training SQLite D

20 Dec 27, 2022
Group Activity Recognition with Clustered Spatial Temporal Transformer

GroupFormer Group Activity Recognition with Clustered Spatial-TemporalTransformer Backbone Style Action Acc Activity Acc Config Download Inv3+flow+pos

28 Dec 12, 2022
[ACMMM 2021 Oral] Enhanced Invertible Encoding for Learned Image Compression

InvCompress Official Pytorch Implementation for "Enhanced Invertible Encoding for Learned Image Compression", ACMMM 2021 (Oral) Figure: Our framework

96 Nov 30, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Shigang Li 9 Oct 29, 2022
Hands-On Machine Learning for Algorithmic Trading, published by Packt

Hands-On Machine Learning for Algorithmic Trading Hands-On Machine Learning for Algorithmic Trading, published by Packt This is the code repository fo

Packt 981 Dec 29, 2022
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes (CVPR 2021 Oral)

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Surfaces Official code release for NGLOD. For technical details, please refer t

659 Dec 27, 2022
Code for How To Create A Fully Automated AI Based Trading System With Python

AI Based Trading System This code works as a boilerplate for an AI based trading system with yfinance as data source and RobinHood or Alpaca as broker

Rubén 196 Jan 05, 2023
PyTorch implementation of DCT fast weight RNNs

DCT based fast weights This repository contains the official code for the paper: Training and Generating Neural Networks in Compressed Weight Space. T

Kazuki Irie 4 Dec 24, 2022
DeepAL: Deep Active Learning in Python

DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin

Kuan-Hao Huang 583 Jan 03, 2023