LabelMe图像数据集下载
Download MATLAB Toolbox for the LabelMe Image Database
利用Matlab Toolbox工具箱下载图像库
一、下载Matlab Toolbox工具箱
1. Github repository
We maintain the latest version of the toolbox on github. To pull the latest version, make sure that "git" is installed on your machine and then run "git clone https://github.com/CSAILVision/LabelMeToolbox.git" on the command line. You can refresh your copy to the latest version by running "git pull" from inside the project directory.
2. Zip file
The zip file is a snapshot of the latest source code on github.
二、下载图像库
Download the Dataset
There are two ways to work with the dataset: (1) downloading all the images via the LabelMe Matlab toolbox. The toolbox will allow you to customize the portion of the database that you want to download, (2) Using the images online via the LabelMe Matlab toolbox. This option is less preferred as it will be slower, but it will allow you to explore the dataset before downloading it. Once you have installed the database, you can use the LabelMe Matlab toolbox to read the annotation files and query the images to extract specific objects.
Option 1: Customizable download using the LabelMe Matlab toolbox
Before downloading the dataset, we only ask you to label some images using the annotation tool online. Any new labels that you will add, will be inmediately ready for download.
Step 1: Download the LabelMe Matlab toolbox and add the toolbox to the Matlab path.
Step 2: The function LMinstall will download the database. There are three ways to use this function:
- To download the entire dataset, type the following into Matlab:
HOMEIMAGES = '/desired/path/to/Images';
HOMEANNOTATIONS = '/desired/path/to/Annotations';
LMinstall (HOMEIMAGES, HOMEANNOTATIONS); where "/desired/path/to/" is the desired location where the annotations and images will be stored.
This process will create the following directory structure under "/desired/path/to/":
./Annotations
./Annotations/folder1
...
./Annotations/folderN ./Images
./Images/folder1
...
./Images/folderN where folder1 through folderN are directories containing the images and annotations.
- If you only want to download a list of specific folders, then run:
HOMEIMAGES = '/desired/path/to/Images';
HOMEANNOTATIONS = '/desired/path/to/Annotations';
folderlist = {'05june05_static_street_porter'};
LMinstall (folderlist, HOMEIMAGES, HOMEANNOTATIONS);
This will download only one folder from the collection. You can see the complete list of folders here.
- If you already have the dataset but want to update the annotations, then use LMinstall with four arguments:
LMinstall (folders, images, HOMEIMAGES, HOMEANNOTATIONS);
Option 2: Access the online database directly with the LabelMe Matlab toolbox
Before downloading the dataset, we only ask you to label some images using the annotation tool online. Any new labels that you will add, will be inmediately ready for download. If you use the LabelMe Matlab toolbox, it is not necesary to download the database. You can use the online images and annotations in the same way as if they were on your local hard drive. This might be slow, but it will let you explore the database before downloading it. If you plan to use the database extensively, it is better to download a local copy for yourself. Here are a few Matlab commands that show how to use the online database:
HOMEIMAGES = 'http://people.csail.mit.edu/brussell/research/LabelMe/Images';
HOMEANNOTATIONS = 'http://people.csail.mit.edu/brussell/research/LabelMe/Annotations'; D = LMdatabase(HOMEANNOTATIONS); % This will build an index, which will take few minutes. % Now you can visualize the images
LMplot(D, , HOMEIMAGES); % Or read an image
[annotation, img] = LMread(D, , HOMEIMAGES);
You can query the database to select the images you want and install only those ones. For instance, if you are interested only in images containing cars, you can run the following:
% First create the list of images that you want:
[Q,j] = LMquery(D, 'object.name', 'car');
clear folderlist filelist
for i = :length(Q);
folderlist{i} = Q(i).annotation.folder;
filelist{i} = Q(i).annotation.filename;
end % Install the selected images:
HOMEIMAGES = '/desired/path/to/Images';
HOMEANNOTATIONS = '/desired/path/to/Annotations';
LMinstall (folderlist, filelist, HOMEIMAGES, HOMEANNOTATIONS);
参考:
[1] http://labelme.csail.mit.edu/Release3.0/browserTools/php/matlab_toolbox.php
[2] http://labelme.csail.mit.edu/Release3.0/browserTools/php/dataset.php
LabelMe图像数据集下载的更多相关文章
- SUN dataset图像数据集下载
SUN dataset数据集,有两个不错的网址: http://vision.princeton.edu/projects/2010/SUN/ (普林斯顿大学) http://groups.csail ...
- 人工智能大数据,公开的海量数据集下载,ImageNet数据集下载,数据挖掘机器学习数据集下载
人工智能大数据,公开的海量数据集下载,ImageNet数据集下载,数据挖掘机器学习数据集下载 ImageNet挑战赛中超越人类的计算机视觉系统微软亚洲研究院视觉计算组基于深度卷积神经网络(CNN)的计 ...
- 医学图像数据(二)——TCIA完整数据集下载方式
1. 构建下载环境 l TCIA数据集下载文件为.jnlp格式(JNLP(Java Network Launching Protocol )是java提供的一种可以通过浏览器直接执行java应用程序 ...
- scikit-learn数据集下载太慢的问题
有时候用scikit-learn在线下载数据时太慢,因为网络或者其他原因,这时候我们可以先把数据集下载到本地,然后再把这个数据集放到scikit-learn的data中,首先我们需要找到 scikit ...
- MS coco数据集下载
2017年12月02日 23:12:11 阅读数:10411 登录ms-co-co数据集官网,一直不能进入,FQ之后开看到下载链接.有了下载链接下载还是很快的,在我这儿晚上下载,速度能达到7M/s,所 ...
- Kaggle数据集下载
Kaggle数据集下载步骤: 安装Kaggle库: 注册Kaggle账户: 找到数据集,接受rules: 在My Account>>API中,点击Create New API Token, ...
- MIR Flickr 1M 图像数据集(点击即可下载)
Index of /mirflickr/mirflickr1m Name Last modified Size Description Parent Directory - exif.zip ...
- zhuan 常用图像数据集:标注、检索
目录(?)[+] 1.搜狗实验室数据集: http://www.sogou.com/labs/dl/p.html 互联网图片库来自sogou图片搜索所索引的部分数据.其中收集了包括人物.动物. ...
- 【机器学习】【计算机视觉】非常全面的图像数据集《Actions》
目录(?)[+] 1.搜狗实验室数据集: http://www.sogou.com/labs/dl/p.html 互联网图片库来自sogou图片搜索所索引的部分数据.其中收集了包括人物.动物.建筑 ...
随机推荐
- 【转载】CreateProcess的用法
第一.第二个参数的用法: 例子: 使用ie打开指定的网页. 注意第二个参数是 可执行文件+命令行参数 #include "stdafx.h" #include <window ...
- mingw fbx sdk /浮点数精度
接下来要做一个linux下的程序了. 下载linux version fbx sdk tar zxvf ...gz 按照安装说明 提升权限并没什么用 还是,cannot execute bin ...
- 查看windows系统热键占用情况
有时候我们经常用一些软件中的快捷键,但是会发现快捷键设置的很正确,但是就是不起作用.这就是因为这些快捷键被系统或者其他软件占用了. 那么这时我们怎么知道是哪个软件占用了呢?这确实是个纠结的问题,还好大 ...
- linux下安装vsftp
1. yum安装vsftp # yum install vsftpd 2. 配置Vsftpd 安装完之后我们要对它进行配置,才能正常使用.编辑vsftpd的配置文件vi /etc/vsftpd/vsf ...
- Altium Designer 使用小结
今天刚把做好的PCB文件交给工厂去制板,阶段工作告一段落,来一个小总结. 前一段时间复习完C语言之后,在中国知网上搜索用单片机实现的小制作,找比较有意思,又不需要太多外专业知识的东西,然后就相中了超声 ...
- Environment.SpecialFolder.CommonApplicationData
private void button1_Click(object sender, EventArgs e) { var path=Environment.GetFolderPath(Environm ...
- ASP.NET中的事件处理
一.ASP.NET中的事件主要支持3个主要的事件组:1.包含在asp.net生成页面时自动生成,我们使用这些事件建立页面(如page_load等)2.包含了用户与页面交互时发生的所有事件(这种最强大) ...
- Javacript中(function(){})() 与 (function(){}()) 区别 {转}
这个问题可以从不同的角度来看,但从结果上来说 :他们是一样的.首先,如果从AST(抽象语法树)的角度来看,两者的AST是一模一样的,最终结果都是一次函数调用.因此,就解析器产生的结果论而言,两者是没有 ...
- 从3D Studio Max导入物体 Importing Objects From 3D Studio Max
原地址:http://game.ceeger.com/Manual/HOWTO-ImportObjectMax.html If you make your 3D objects in 3dsMax, ...
- lightoj 1408 Batting Practice (概率问题,求期望,推公式)
题意:一个人若连续进k1个球或连续不进k2个球,游戏结束,给出这个人不进球的概率p(注意:是不进球!!!),求到游戏结束时这个投球个数的期望. 不进球概率为p,进概率 q=1-p.设 f[i] 表示连 ...