buildseg is a building extraction plugin of QGIS based on PaddlePaddle.

Overview

buildseg

Python 3.8 PaddlePaddle 2.2 QGIS 3.16.11

buildseg is a Building Extraction plugin for QGIS based on PaddlePaddle.

fds

How to use

  1. Download and install QGIS and clone the repo :
git clone [email protected]:geoyee/buildseg.git
  1. Install requirements :

    • Enter the folder and install dependent libraries using OSGeo4W shell (Open As Administrator) :
    cd buildseg
    pip install -r requirements.txt
    • Or open OSGeo4W shell as administrator and enter :
    pip install opencv-python paddlepaddle>=2.2.0 paddleseg --user
  2. Copy folder named buildseg in QGIS configuration folder and choose the plugin from plugin manager in QGIS (If not appeared restart QGIS).

    • You can know this folder from QGIS Setting Menu at the top-left of QGIS UI Settings > User Profiles > Open Active Profile Folder .
    • Go to python/plugins then paste the buildseg folder.
    • Full path should be like : C:\Users\$USER\AppData\Roaming\QGIS\QGIS3\profiles\default\python\plugins\buildseg.
  3. Open QGIS, load your raster and select the parameter file (*.pdiparams) then click ok.

Model and Parameter

Model Backbone Resolution mIoU Params(MB) Inference Time(ms) Links
OCRNet HRNet_W18 512x512 90.64% 46.4 / Static Weight
  • Train/Eval Dataset : Link.
  • We have done all testing and development using : Tesla V100 32G in AI Studio.

TODO

  • Extract building on 512x512 remote sensing images.
  • Extract building on big remote sensing images through splitting it into small tiles, extract buildings then mosaic it back (merge) to a full extent.
  • Replace the model and parameters (large-scale data).
  • Convert to static weight (*.pdiparams) instead of dynamic model (*.pdparams).
  • Add a Jupyter Notebook (*.ipynb) about how to fine-tune parameters using other's datasets based on PaddleSeg.
  • Hole digging inside the polygons.
  • Convert raster to Shapefile/GeoJson by GDAL/OGR (gdal.Polygonize) instead of findContours in OpenCV.
  • Update plugin's UI :
    • Add menu to select one raster file from QGIS opened raster layers.
    • Select the Parameter path one time (some buggy windows appear when importing the *.pdiparams file).
    • Define the output path of the vector file (Direct Path or Temporary in the memory).
    • Add setting about used GPU / block size and overlap size.
  • Accelerate, etc.
  • Add another model, like Vision Transform.
You might also like...
Multi-Modal Machine Learning toolkit based on PaddlePaddle.
Multi-Modal Machine Learning toolkit based on PaddlePaddle.

简体中文 | English PaddleMM 简介 飞桨多模态学习工具包 PaddleMM 旨在于提供模态联合学习和跨模态学习算法模型库,为处理图片文本等多模态数据提供高效的解决方案,助力多模态学习应用落地。 近期更新 2022.1.5 发布 PaddleMM 初始版本 v1.0 特性 丰富的任务

Awesome Remote Sensing Toolkit based on PaddlePaddle.
Awesome Remote Sensing Toolkit based on PaddlePaddle.

基于飞桨框架开发的高性能遥感图像处理开发套件,端到端地完成从训练到部署的全流程遥感深度学习应用。 最新动态 PaddleRS 即将发布alpha版本!欢迎大家试用 简介 PaddleRS是遥感科研院所、相关高校共同基于飞桨开发的遥感处理平台,支持遥感图像分类,目标检测,图像分割,以及变化检测等常用遥

A PaddlePaddle version image model zoo.

Paddle-Image-Models English | 简体中文 A PaddlePaddle version image model zoo. Install Package Install by pip: $ pip install ppim Install by wheel package

Plaything for Autistic Children (demo for PaddlePaddle/Wechaty/Mixlab project)
Plaything for Autistic Children (demo for PaddlePaddle/Wechaty/Mixlab project)

星星的孩子 - 一款为孤独症孩子设计的聊天机器人游戏 孤独症儿童是目前常常被忽视的一类群体。他们有着类似性格内向的特征,实际却受着广泛性发育障碍的折磨。 项目背景 这类儿童在与人交往时存在着沟通障碍,其特点表现在: 社交交流差,互动障碍明显 认知能力有限,被动认知 兴趣狭窄,重复刻板,缺乏变化和想象

Official PaddlePaddle implementation of Paint Transformer
Official PaddlePaddle implementation of Paint Transformer

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Paddle Implementation] Update We have optimized the serial inference p

An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.
An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.

简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型,分别是SimpleCNN和MiniXception。利用 imdb_crop

PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or

🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Comments
  • QGIS crashes in startup of the plugin on Linux/Ubuntu

    QGIS crashes in startup of the plugin on Linux/Ubuntu

    Bug with Linux/Debian/Ubuntu image

    and when installing raspberry bi deps image

    it just crashes when trying to import paddle (in QGIS Python script window) without trying to install the plugin

    Tried on Ubuntu 18.04 and 20.04

    bug solved 
    opened by Youssef-Harby 4
  • Use ONNX

    Use ONNX

    please check this branch, test in Mac OS and update README / README_CN (☑ On mac OS Big Sur+). if you think we should use this branch rather than develop (use onnx instead of paddle), you can argee with the pr. or not, please write your viewpoint. thank you youssef ☺

    opened by geoyee 2
  • Installation Bug Report: Plugin Error while installation

    Installation Bug Report: Plugin Error while installation

    An error occurred during execution of following code: pyplugin_installer.instance().installPlugin('buildseg', stable=False)

    Traceback (most recent call last): File "", line 1, in File "/usr/share/qgis/python/pyplugin_installer/installer.py", line 333, in installPlugin self.processDependencies(plugin["id"]) File "/usr/share/qgis/python/pyplugin_installer/installer.py", line 682, in processDependencies dlg = QgsPluginDependenciesDialog(plugin_id, to_install, to_upgrade, not_found) File "/usr/share/qgis/python/pyplugin_installer/qgsplugindependenciesdialog.py", line 92, in init _make_row(data, i, name) File "/usr/share/qgis/python/pyplugin_installer/qgsplugindependenciesdialog.py", line 63, in _make_row widget.use_stable_version = data['use_stable_version'] KeyError: 'use_stable_version'

    Python version: 3.8.10 (default, Nov 26 2021, 20:14:08) [GCC 9.3.0]

    QGIS version: 3.22.3-Białowieża 'Białowieża', 1628765ec7

    Python path: ['/usr/share/qgis/python', '/home/robotics/.local/share/QGIS/QGIS3/profiles/default/python', '/home/robotics/.local/share/QGIS/QGIS3/profiles/default/python/plugins', '/usr/share/qgis/python/plugins', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/robotics/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages', '/home/robotics/.local/share/QGIS/QGIS3/profiles/default/python', '/home/robotics/.local/share/QGIS/QGIS3/profiles/default/python/plugins/DeepLearningTools']

    bug solved 
    opened by makamkkumar 2
  • Installation: using QGIS

    Installation: using QGIS "Manage and Install Plugins", or directions in the md file?

    What is better for Installation: using QGIS "Manage and Install Plugins", or following directions in the md file? Using the QGIS installer (3.24.0-Tisler) I get: An error occurred during execution of following code: pyplugin_installer.instance().installPlugin('buildseg', stable=True)

    Traceback (most recent call last): File "", line 1, in File "/usr/share/qgis/python/pyplugin_installer/installer.py", line 333, in installPlugin self.processDependencies(plugin["id"]) File "/usr/share/qgis/python/pyplugin_installer/installer.py", line 682, in processDependencies dlg = QgsPluginDependenciesDialog(plugin_id, to_install, to_upgrade, not_found) File "/usr/share/qgis/python/pyplugin_installer/qgsplugindependenciesdialog.py", line 92, in init _make_row(data, i, name) File "/usr/share/qgis/python/pyplugin_installer/qgsplugindependenciesdialog.py", line 63, in _make_row widget.use_stable_version = data['use_stable_version'] KeyError: 'use_stable_version'

    Python version: 3.9.5 (default, Nov 18 2021, 16:00:48) [GCC 10.3.0]

    QGIS version: 3.24.0-Tisler 'Tisler', 6b44a42058

    Python path: ['/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/terminus_processing', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/LAStools', '/usr/share/qgis/python', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins', '/usr/share/qgis/python/plugins', '/home/alobo/OTB/OTB-7.3.0-Linux64/lib/python', '/usr/lib/python39.zip', '/usr/lib/python3.9', '/usr/lib/python3.9/lib-dynload', '/home/alobo/.local/lib/python3.9/site-packages', '/usr/local/lib/python3.9/dist-packages', '/usr/lib/python3/dist-packages', '/usr/lib/python3.9/dist-packages', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python', '.', '/home/alobo/.local/lib/python3.9/site-packages/IPython/extensions', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin/site-packages', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin/enmapbox/qgispluginsupport/qps/pyqtgraph', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin/enmapbox/site-packages', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin/enmapbox/apps', '/home/alobo/.local/share/QGIS/QGIS3/profiles/default/python/plugins/enmapboxplugin/enmapbox/coreapps']

    bug 
    opened by aloboa 3
Releases(v0.3.1)
Demonstrates iterative FGSM on Apple's NeuralHash model.

apple-neuralhash-attack Demonstrates iterative FGSM on Apple's NeuralHash model. TL;DR: It is possible to apply noise to CSAM images and make them loo

Lim Swee Kiat 11 Jun 23, 2022
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records

HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro

Hanyang Liu 4 Aug 08, 2022
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

DK 96 Jan 06, 2023
Real-Time Semantic Segmentation in Mobile device

Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur

708 Jan 01, 2023
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"

Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal

Planet AI GmbH 9 May 20, 2022
This is the repo of the manuscript "Dual-branch Attention-In-Attention Transformer for speech enhancement"

DB-AIAT: A Dual-branch attention-in-attention transformer for single-channel SE

Guochen Yu 68 Dec 16, 2022
LLVM-based compiler for LightGBM gradient-boosted trees. Speeds up prediction by ≥10x.

LLVM-based compiler for LightGBM gradient-boosted trees. Speeds up prediction by ≥10x.

Simon Boehm 183 Jan 02, 2023
STMTrack: Template-free Visual Tracking with Space-time Memory Networks

STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac

Zhihong Fu 62 Dec 21, 2022
Pseudo-Visual Speech Denoising

Pseudo-Visual Speech Denoising This code is for our paper titled: Visual Speech Enhancement Without A Real Visual Stream published at WACV 2021. Autho

Sindhu 94 Oct 22, 2022
Bayesian optimization in PyTorch

BoTorch is a library for Bayesian Optimization built on PyTorch. BoTorch is currently in beta and under active development! Why BoTorch ? BoTorch Prov

2.5k Dec 31, 2022
Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch

SRDenseNet-pytorch Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch (http://openaccess.thecvf.com/content_ICC

wxy 114 Nov 26, 2022
Machine Unlearning with SISA

Machine Unlearning with SISA Lucas Bourtoule, Varun Chandrasekaran, Christopher Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, N

CleverHans Lab 70 Jan 01, 2023
Repository for paper "Non-intrusive speech intelligibility prediction from discrete latent representations"

Non-Intrusive Speech Intelligibility Prediction from Discrete Latent Representations Official repository for paper "Non-Intrusive Speech Intelligibili

Alex McKinney 5 Oct 25, 2022
MG-GCN: Scalable Multi-GPU GCN Training Framework

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

Translational Data Analytics (TDA) Lab @GaTech 6 Oct 24, 2022
Calculates JMA (Japan Meteorological Agency) seismic intensity (shindo) scale from acceleration data recorded in NumPy array

shindo.py Calculates JMA (Japan Meteorological Agency) seismic intensity (shindo) scale from acceleration data stored in NumPy array Introduction Japa

RR_Inyo 3 Sep 23, 2022
A lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look At CoefficienTs)

Real-time Instance Segmentation and Lane Detection This is a lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look

Jin 4 Dec 30, 2022
This is 2nd term discrete maths project done by UCU students that uses backtracking to solve various problems.

Backtracking Project Sponsors This is a project made by UCU students: Olha Liuba - crossword solver implementation Hanna Yershova - sudoku solver impl

Dasha 4 Oct 17, 2021
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

196 Jan 05, 2023
Benchmarking the robustness of Spatial-Temporal Models

Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal

Yi Chenyu Ian 15 Dec 16, 2022
MAterial del programa Misión TIC 2022

Mision TIC 2022 Esta iniciativa, aparece como respuesta frente a los retos de la Cuarta Revolución Industrial, y tiene como objetivo la formación de 1

6 May 25, 2022