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Home > FreeData Preview > SceneSegmentation_18
 
Dataset 7 LHI_SceneSegmentation_18
Contents and Statistics :
Category Subcategory
Number of Images
Free
Total
Outdoor(8) street
15
11363
seashore
15
305
rural
15
57
parking
15
8452
natrual landscape
15
1360
highway
15
398
harbor
9
773
cityview
15
338
Indoor(6) office
15
765
livingroom
15
1389
hall
15
775
corridor
15
240
bedroom
15
9816
bathroom
15
1870
Activity(4) sports
15
844
Shop
15
299
meeting
15
229
lecture
15
572
Matlab codes to load this category (see MatlabToolbox page for more information):
clear; close all;
HOMEIMAGES = 'C:\Yourdatabase\LHI_SceneSegmentation_20\Images';
% set your folder
HOMEANNOTATIONS = 'C:\Yourdatabase\LHI_SceneSegmentation_20\Annotations';
HOMELABELMAPS = 'C:\Yourdatabase\LHI_SceneSegmentation_20\LabelMaps';

Code to load the database and mapping the names
rawDB = LHIdatabase(HOMEANNOTATIONS); %To load the database
NEWHOMELABELMAPS = 'C:/temp/yourposition/'; %folder to store regulated labelmap
D=LHIregulatenames(rawDB,HOMELABELMAPS,NEWHOMELABELMAPS,'Sport_names.txt'); %name translation, you can define your own name translation dictionary by modifying Sport_names.txt

 


Code to produce the figure below:
LHIobjectnames(D); %show object frequency

Figure 1 Object frequency count

View one image for hierarchical decomposition
Code to produce the figure:
LHIdbshowscenes(D(ind),HOMEIMAGES); %Display category image
Figure 2. Hierarchical decomposition of an image

Statistics of the category
General statistics including number of keypoints on the boundary for each object, sum of object/image area ratio. Position (x,y axis of center point) histogram.
Code to produce figure:
[objectnames, instancecounts, areacounts, pointcounts, positions]=LHIobjectstats(D, HOMEIMAGES, NEWHOMELABELMAPS);
Figure 3 Histogram of the number of key points used to define each object
Figure 4. Histogram of the percentage of pixels occupied (relative to the image size) by each object instance
Figure 5. This plot shows the distribution of locations occupied by each instance. Each dot corresponds to the original location, relative to the image frame, of each object instance. These plots help to understand some of the biases that the photographers might have when taking pictures of specific objects.


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