FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification

Related tags

Deep Learningcomputer-visiondeep-learninggeospatialremote-sensingconvolutional-neural-networkhyperspectral-image-classification
Overview

PWC

PWC

PWC

License: GPL v3

FPGA & FreeNet

Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
by Zhuo Zheng, Yanfei Zhong, Ailong Ma and Liangpei Zhang


This is an official implementation of FPGA framework and FreeNet in our TGRS 2020 paper "FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification".

We hope the FPGA framework can become a stronger and cleaner baseline for hyperspectral image classification research in the future.

News

  1. 2020/05/28, We release the code of FreeNet and FPGA framework.

Features

  1. Patch-free training and inference
  2. Fully end-to-end (w/o preprocess technologies, such as dimension reduction)

Citation

If you use FPGA framework or FreeNet in your research, please cite the following paper:

@article{zheng2020fpga,
  title={FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification},
  author={Zheng, Zhuo and Zhong, Yanfei and Ma, Ailong and Zhang, Liangpei},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2020},
  publisher={IEEE},
  note={doi: {10.1109/TGRS.2020.2967821}}
}

Getting Started

1. Install SimpleCV

pip install --upgrade git+https://github.com/Z-Zheng/SimpleCV.git

2. Prepare datasets

It is recommended to symlink the dataset root to $FreeNet.

The project should be organized as:

FreeNet
├── configs     // configure files
├── data        // dataset and dataloader class
├── module      // network arch.
├── scripts 
├── pavia       // data 1
│   ├── PaviaU.mat
│   ├── PaviaU_gt.mat
├── salinas     // data 2
│   ├── Salinas_corrected.mat
│   ├── Salinas_gt.mat
├── GRSS2013    // data 3
│   ├── 2013_IEEE_GRSS_DF_Contest_CASI.tif
│   ├── train_roi.tif
│   ├── val_roi.tif

3. run experiments

1. PaviaU

bash scripts/freenet_1_0_pavia.sh

2. Salinas

bash scripts/freenet_1_0_salinas.sh

3. GRSS2013

bash scripts/freenet_1_0_grss.sh

License

This source code is released under GPLv3 license.

For commercial use, please contact Prof. Zhong ([email protected]).

Projects using FPGA/FreeNet

Welcome to pull request if you use this repo as your codebase.

You might also like...
End-to-End Object Detection with Fully Convolutional Network
End-to-End Object Detection with Fully Convolutional Network

This project provides an implementation for "End-to-End Object Detection with Fully Convolutional Network" on PyTorch.

null 472 Dec 22, 2022
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering
Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Yaoming Cai 5 Jul 18, 2022
Global Filter Networks for Image Classification
Global Filter Networks for Image Classification

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

Yongming Rao 273 Dec 26, 2022
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

XCL 191 Dec 31, 2022
⚡ Fast • 🪶 Lightweight • 0️⃣ Dependency • 🔌 Pluggable • 😈 TLS interception • 🔒 DNS-over-HTTPS • 🔥 Poor Man's VPN • ⏪ Reverse & ⏩ Forward • 👮🏿
⚡ Fast • 🪶 Lightweight • 0️⃣ Dependency • 🔌 Pluggable • 😈 TLS interception • 🔒 DNS-over-HTTPS • 🔥 Poor Man's VPN • ⏪ Reverse & ⏩ Forward • 👮🏿 "Proxy Server" framework • 🌐 "Web Server" framework • ➵ ➶ ➷ ➠ "PubSub" framework • 👷 "Work" acceptor & executor framework

Table of Contents Features Install Using PIP Stable version Development version Using Docker Stable version Development version Using HomeBrew Stable

Abhinav Singh 2.2k Jan 8, 2023
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).

Salesforce 334 Jan 6, 2023
Simple-Image-Classification - Simple Image Classification Code (PyTorch)
Simple-Image-Classification - Simple Image Classification Code (PyTorch)

Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima

Yechan Kim 8 Oct 29, 2022
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

null 0 Jan 23, 2022
Comments
  • Some issues about the code.

    Some issues about the code.

    I try to run your code on the Pavia data set.

    Traceback (most recent call last): File "d:/FreeNet-master/train.py", line 63, in opts=args.opts) File "D:\software\anaconda\lib\site-packages\simplecv\dp_train.py", line 44, in run traindata_loader = make_dataloader(cfg['data']['train']) File "D:\software\anaconda\lib\site-packages\simplecv\data\data_loader.py", line 9, in make_dataloader raise ValueError('{} is not support now.'.format(dataloader_type)) ValueError: NewPaviaLoader is not support now.

    Looking forward to hearing from you!

    opened by zhe-meng 2
  • Test.py module

    Test.py module

    Hello!

    I really appreciate your paper and sharing the code for it. I wonder is there an option to make a test on the trainned network on another image? I saw test dict in config file, but I'm not sure it is implemented for now. Is there any plans for it or will you please suggest how can it be done better?

    Thanks!

    opened by valeriylo 0
  • 运行 train.py时报错

    运行 train.py时报错

    Traceback (most recent call last): File "D:/论文代码书/代码/高光谱影像分类/全卷积FCN/FreeNet-master/train.py", line 60, in train.run(config_path=args.config_path, File "D:\Anaconda\envs\Pytorch\lib\site-packages\simplecv-0.3.4-py3.8.egg\simplecv\dp_train.py", line 29, in run cfg = config.import_config(config_path) File "D:\Anaconda\envs\Pytorch\lib\site-packages\simplecv-0.3.4-py3.8.egg\simplecv\util\config.py", line 5, in import_config m = importlib.import_module(name='{}.{}'.format(prefix, config_name)) File "D:\Anaconda\envs\Pytorch\lib\importlib_init_.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1014, in _gcd_import File "", line 991, in _find_and_load File "", line 973, in _find_and_load_unlocked ModuleNotFoundError: No module named 'configs.None'

    opened by Zhengpu-L 1
  • 在安装simpleCV时出现报错

    在安装simpleCV时出现报错

    您好，我在终端安装simpleCV时出现了以下报错: ERROR: Could not find a version that satisfies the requirement tensorboardX==1.7 (from simplecv) (from versions: none) ERROR: No matching distribution found for tensorboardX==1.7 请问您知道如何解决吗，simpleCV是基于tensorflow框架的吗，但freenet好像是基于pytorch，很抱歉打扰您

    opened by wangk98 3
Releases(v1.2)
Owner
Zhuo Zheng
CV IN RS. Ph.D. Student.
Zhuo Zheng
GitHub Repository
Deeplab-resnet-101 in Pytorch with Jaccard loss

Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:

Maxim Berman 95 Apr 15, 2022
An educational resource to help anyone learn deep reinforcement learning.

Status: Maintenance (expect bug fixes and minor updates) Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that ma

OpenAI 7.6k Jan 09, 2023
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification

Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv

陈志豪 8 Oct 13, 2022
The official implementation of ICCV paper "Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds".

Box-Aware Tracker (BAT) Pytorch-Lightning implementation of the Box-Aware Tracker. Box-Aware Feature Enhancement for Single Object Tracking on Point C

Kangel Zenn 5 Mar 26, 2022
Realtime micro-expression recognition using OpenCV and PyTorch

Micro-expression Recognition Realtime micro-expression recognition from scratch using OpenCV and PyTorch Try it out with a webcam or video using the e

Irfan 35 Dec 05, 2022
Async API for controlling Hue Lights

Hue API Async API for controlling Hue Lights Documentation: hue-api.nirantak.com Source: github.com/nirantak/hue-api Installation This is an async cli

Nirantak Raghav 4 Nov 16, 2022
Establishing Strong Baselines for TripClick Health Retrieval; ECIR 2022

TripClick Baselines with Improved Training Data Welcome 🙌 to the hub-repo of our paper: Establishing Strong Baselines for TripClick Health Retrieval

Sebastian Hofstätter 3 Nov 03, 2022
A library that can print Python objects in human readable format

objprint A library that can print Python objects in human readable format Install pip install objprint Usage op Use op() (or objprint()) to print obj

319 Dec 25, 2022
This repository contains the data and code for the paper "Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors" ([email protected])

GP-VAE This repository provides datasets and code for preprocessing, training and testing models for the paper: Diverse Text Generation via Variationa

Wanyu Du 18 Dec 29, 2022
Object detection (YOLO) with pytorch, OpenCV and python

Real Time Object/Face Detection Using YOLO-v3 This project implements a real time object and face detection using YOLO algorithm. You only look once,

1 Aug 04, 2022
Code of TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

TVT Code of TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation Datasets: Digit: MNIST, SVHN, USPS Object: Office, Office-Home, Vi

37 Dec 15, 2022
CTF challenges from redpwnCTF 2021

redpwnCTF 2021 Challenges This repository contains challenges from redpwnCTF 2021 in the rCDS format; challenge information is in the challenge.yaml f

redpwn 27 Dec 07, 2022
Use AI to generate a optimized stock portfolio

Use AI, Modern Portfolio Theory, and Monte Carlo simulation's to generate a optimized stock portfolio that minimizes risk while maximizing returns. Ho

Greg James 30 Dec 22, 2022
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

CFC-Net This project hosts the official implementation for the paper: CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Dete

ming71 55 Dec 12, 2022
An All-MLP solution for Vision, from Google AI

MLP Mixer - Pytorch An All-MLP solution for Vision, from Google AI, in Pytorch. No convolutions nor attention needed! Yannic Kilcher video Install $ p

Phil Wang 784 Jan 06, 2023
Fast, flexible and easy to use probabilistic modelling in Python.

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

Jacob Schreiber 3k Dec 29, 2022
A python package to perform same transformation to coco-annotation as performed on the image.

coco-transform-util A python package to perform same transformation to coco-annotation as performed on the image. Installation Way 1 $ git clone https

1 Jan 14, 2022
Blender scripts for computing geodesic distance

GeoDoodle Geodesic distance computation for Blender meshes Table of Contents Overivew Usage Implementation Overview This addon provides an operator fo

20 Jun 08, 2022
🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.

OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th

Gustavo Rosa 30 Jan 04, 2023
Try out deep learning models online on Google Colab

Try out deep learning models online on Google Colab

Erdene-Ochir Tuguldur 1.5k Dec 27, 2022