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geoyee committed Dec 13, 2021
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3 changes: 1 addition & 2 deletions README.md
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buildseg is a Building Extraction plugin for QGIS based on PaddlePaddle, and it useing the semantic segmentation ability provided by paddleseg, large areas can be extracted and spliced.

![fds](https://user-images.githubusercontent.com/71769312/144746418-cdbb2d5a-32f8-49e3-bc42-d5d2d3e6810f.gif)
![bs001](https://user-images.githubusercontent.com/71769312/145813120-b1f20a02-94da-436d-b8ec-d523bcccb720.gif)

## How to use

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| :----------: | :-------: | :--------: | :----: | :--------: | :----------------: | :----------------------------------------------------------: |
| OCRNet | HRNet_W18 | 512x512 | 89.38% | 46.2 | / | [Static Weight](https://cloud.a-boat.cn:2021/share/ot6D3FyY) |
| SegFormer_B2 | - | 512x512 | / | / | / | / |
| HarDNet | - | 512x512 | / | / | / | / |

- Train/Eval(5k) Dataset : [Link](https://aistudio.baidu.com/aistudio/datasetdetail/102929).
- We have done all testing and development using : Tesla V100 32G in [AI Studio](https://aistudio.baidu.com/aistudio/index).
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3 changes: 1 addition & 2 deletions docs/README_CN.md
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[![Python 3.8](https://img.shields.io/badge/python-3.8-yellow.svg)](https://www.python.org/downloads/release/python-380/) [![PaddlePaddle 2.2](https://img.shields.io/badge/paddlepaddle-2.2+-blue.svg)](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/windows-pip.html) [![QGIS 3.16.11](https://img.shields.io/badge/qgis-3.16.11+-green.svg)](https://www.qgis.org/) ![license](https://img.shields.io/github/license/deepbands/buildseg) ![release](https://img.shields.io/badge/release-v0.1-red.svg)

buildseg是一个基于PaddlePaddle的用于建筑提取的QGIS插件,使用PaddleSeg提供的语义分割能力,可以对大片区域进行分块提取并拼接。
![bs001](https://user-images.githubusercontent.com/71769312/145813120-b1f20a02-94da-436d-b8ec-d523bcccb720.gif)

![fds](https://user-images.githubusercontent.com/71769312/144746418-cdbb2d5a-32f8-49e3-bc42-d5d2d3e6810f.gif)

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| :----------: | :-------: | :-----: | :--------: | :------: | :----------: | :-----------------------------------------------------: |
| OCRNet | HRNet_W18 | 512x512 | 89.38% | 46.2 | / | [静态权重](https://cloud.a-boat.cn:2021/share/ot6D3FyY) |
| SegFormer_B2 | - | 512x512 | / | / | / | / |
| HarDNet | - | 512x512 | / | / | / | / |

- 训练和评估(5千) 数据集:[链接](https://aistudio.baidu.com/aistudio/datasetdetail/102929)。
- 训练和评估使用 : [AI Studio](https://aistudio.baidu.com/aistudio/index)提供的32G的Tesla V100。
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