LEVIR-CD
LEVIR-CD is a new large-scale remote sensing binary change detection dataset, which would help develop novel deep learning-based algorithms for remote sensing image change detection.
Overview of LEVIR-CD
LEVIR-CD is a new large-scale remote sensing building Change Detection dataset. The introduced dataset would be a new benchmark 提供外汇交易商Binary简介 for evaluating change detection (CD) algorithms, 提供外汇交易商Binary简介 especially those based on deep learning.
LEVIR-CD consists of 637 very high-resolution (VHR, 0.5m/pixel) Google Earth (GE) image patch pairs with a size of 1024 × 1024 pixels. These bitemporal images with time span of 5 to 14 years have significant land-use changes, especially the construction growth. LEVIR-CD covers various types of buildings, such as villa residences, tall apartments, small garages and large warehouses. Here, we focus on building-related changes, including the building growth (the change from soil/grass/hardened ground or building under construction to new build-up regions) and the building decline. These bitemporal images are annotated by remote sensing image interpretation experts using binary labels (1 for change and 0 for unchanged). Each sample in our dataset is annotated by one annotator 提供外汇交易商Binary简介 and then double-checked by another to produce high-quality annotations. The fully annotated LEVIR-CD contains a total of 31,333 individual change building instances.
Geospatial Distribution of LEVIR-CD
The bitemporal images in LEVIR-CD are from 20 different regions 提供外汇交易商Binary简介 that sit in several cities in Texas of the US, including Austin, Lakeway, Bee Cave, Buda, Kyle, Manor, Pflugervilletx, Dripping Springs, etc. The Figure below illustrates the geospatial distribution of our new dataset and an enlarged image patch. The captured time of our image data varies from 2002 to 2018. Images in different regions may be taken at different times. We want to introduce variations due to seasonal changes and illumination changes into our new dataset, which could help develop effective methods 提供外汇交易商Binary简介 that can mitigate the impact of irrelevant changes on real changes.
Examples of annotated samples
Samples size of 1024 × 1024
Cropped samples size of 256 × 256
Usage
The use of the images from Google Earth must respect the Google Earth terms of use. All images and annotations in LEVIR-CD can only be used for academic purposes, but are prohibited for any commercial use.
About
We are from LEVIR, which is the abbreviation of ours’ laboratory: LEarning, VIsion and Remote sensing 提供外汇交易商Binary简介 laboratory. Visit the lab homepage for more details.
If you have any the problem or feedback in 提供外汇交易商Binary简介 using LEVIR-CD, please contact
提供外汇交易商Binary简介
BSON（/ˈbiːsən/）是一种计算机数据交换格式，主要被用作MongoDB数据库中的数据存储和网络传输格式。它是一种二进制表示形式，能用来表示简单数据结构、关联数组（MongoDB中称为“对象”或“文档”）以及MongoDB中的各种数据类型。BSON之名缘于JSON，含义为Binary JSON（二进制JSON）。
中文名 BSON 外文名 Binary Serialized Document Format 存储格式 类json的一种二进制形式 例 子 title:"MongoDB", 支 持 内嵌的文档对象和数组对象
BSON 简介
BSON（/ˈbiːsən/）是一种计算机数据交换格式，主要被用作MongoDB数据库中的数据存储和网络传输格式。它是一种二进制表示形式，能用来表示简单数据结构、关联数组（MongoDB中称为“对象”或“文档”）以及MongoDB中的各种数据类型。BSON之名缘于JSON，含义为Binary JSON（二进制JSON）。 [1]
提供外汇交易商Binary简介
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fanvanzh/3dtiles
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README.md
English | 简体中文
Tools for 3D-Tiles convertion.
This 提供外汇交易商Binary简介 is a RUST language project with cpp lib to handle osgb data.
Tools provided are as follow：
Osgb(OpenSceneGraph Binary) to 3D-Tiles : convert huge of osgb file to 3D-Tiles.
Esri Shapefile to 3D-Tiles : convert shapefile to 3D-Tiles.
Fbx to 3D-Tiles : convert fbx file to 3D-Tiles, include auto_lod\texture convertion etc.