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:js动态获取图片长宽尺寸(兼容所有浏览器,速度极快)
转自:http://blog.phpdr.net/js-get-image-size.html lightbox类效果为了让图片居中显示而使用预加载,需要等待完全加载完毕才能显示,体验不佳(如fili ...
- 【Populating Next Right Pointers in Each Node II】cpp
题目: Follow up for problem "Populating Next Right Pointers in Each Node". What if the given ...
- Python 获取学校图书馆OAPC账号对应的身份证号码
import urllib.request import urllib.parse import http.cookiejar import re lib_login = 'http://xxx.ed ...
- Leetcode#128 Longest Consecutive Sequence
原题地址 1. 把所有元素都塞到集合里2. 遍历所有元素,对于每个元素,如果集合里没有,就算了,如果有的话,就向左向右拓展,找到最长的连续范围,同时在每次找的时候都把找到的删掉.这样做保证了同样的连续 ...
- Understanding Convolution in Deep Learning
Understanding Convolution in Deep Learning Convolution is probably the most important concept in dee ...
- 大话C#之属性
前言 俗话说得好:工欲善其事,必先利其器.要想玩转OOP设计出一个优秀的类型,属性是必不可少的,那么我们今天就来说说c#中关于属性的二三事. 属性(property)分为无参属性(parameterl ...
- HDOJ 2152 Fruit(母函数)
Fruit Time Limit: 1000/1000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)Total Submi ...
- Mysql 操作
MySQL命令行导出数据库:1,进入MySQL目录下的bin文件夹:cd MySQL中到bin文件夹的目录如我输入的命令行:cd C:\Program Files\MySQL\MySQL Server ...
- 调用MYSQL存储过程实例
PHP调用MYSQL存储过程实例 http://blog.csdn.net/ewing333/article/details/5906887 http://www.cnblogs.com/kkchen ...
- iOS第三方(显示视图的宽度高度)- MMPlaceHolder
github:https://github.com/adad184/MMPlaceHolder#readme appDelegate添加,影响全局 [MMPlaceHolderConfig defau ...