Last modified by annedevismes on 2021/06/08 11:56

From version 1.5
edited by puchades
on 2020/03/25 14:46
Change comment: There is no comment for this version
To version 2.4
edited by puchades
on 2020/03/25 16:45
Change comment: There is no comment for this version

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9 9  
10 10  As a general rule, pixel classification is suitable for images in which there are clear differences in the colour, intensity and/ or texture of the feature-of-interest versus the background and other structures.  If there is non-specific labelling in the image that is very similar in appearance to the labelling-of-interest, object classification may allow the non-specific labelling to be filtered out based on object level features such as size and shape. The best approach is determined by trial and error.
11 11  
12 +=== Pixel classification workflow ===
12 12  
13 -=== H3 Headings Will Appear In The Table of Content ===
14 +For a quick introduction, watch: [[https:~~/~~/www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be>>url:https://www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be]]
14 14  
15 -==== You can also add images ====
16 +**Basic steps:**
16 16  
17 -[[image:Collaboratory.Apps.Article.Code.ArticleSheet@placeholder.jpg]]
18 +-Train the classifier with two classes (labeling and background)
18 18  
19 -Photo by David Clode
20 +-Apply the classifier to the rest of the images (Batch processing)
20 20  
21 -==== Or code ====
22 +-Export the probability maps in HDH5 format, and simple_segmentation images in .png format, with the default settings.
22 22  
23 -Code blocks can be added by using the code macro:
24 +=== Object classification workflow ===
24 24  
25 -{{code language="python"}}
26 -x = 1
27 -if x == 1:
28 - # indented four spaces
29 - print("x is 1.")
30 -{{/code}}
26 +There are three options on the ilastik start up page for running Object Classification.  Choose the //Object Classification with Raw Data and Pixel Prediction Maps as input//**.**
31 31  
32 -(% class="wikigeneratedid" id="HH4Won27tAppearinToC" %)
28 +-Save the object classification file in the same folder as the raw images for analysis.  If the images are moved after the ilastik file is created, the link between the ilastik file and the images may be lost, resulting in a corrupted file.
29 +
30 +-
31 +
32 +==== ====
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