Last modified by puchades on 2022/09/30 16:01
From version 29.1
edited by tomazvieira
on 2022/02/22 15:30
Change comment: Uploaded new attachment "image-20220222153044-3.png", version {1}
To version 33.1
edited by tomazvieira
on 2022/02/22 16:02
Change comment: There is no comment for this version

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26 26  
27 27  [[image:image-20220128142757-1.png]]
28 28  
29 -=== ===
29 +=== ===
30 30  
31 31  you would type a URL like this:
32 32  
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37 37  
38 38  === Viewing 2D Data ===
39 39  
40 -If your dataset is 2D like in the example, you can click the "switch to xy layout" button at the top-right corner of the top-left quadrant of the viewport to use  asingle, 2D viewport:
40 +If your dataset is 2D like in the example, you can click the "switch to xy layout" button at the top-right corner of the top-left quadrant of the viewport to use a single, 2D viewport:
41 41  
42 42  [[image:image-20220125164416-3.png]]
43 43  
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73 73  
74 74  You must have the "training" tab as the frontmost visible tab in order to start adding brush strokes (in neuroglancer you can click the name of the raw data tab to hide it, for example):
75 75  
76 -[[image:image-20220125170609-3.png]]
76 +[[image:image-20220222151117-1.png]]
77 77  
78 +
78 78  The status display in this applet will show "training on [datasource url]" when you're in training mode.
79 79  
80 80  Now you can start adding brush strokes. Select a color from the color picker, check the "Enable Brushing" checkbox to enable brushing (and disable navigation), and click and drag over the image to add brush strokes. Ilastik will map each used color to a "class", and will try to figure out a class for every pixel in the image based on the examples provided by the brush strokes. By painting, you provide ilastik with samples of what a pixel in that particular class should look like. The following image shows an example with 2 classes: teal, representing the "foreground" or the "cell class", and magenta, representing the "background" class.
81 81  
82 -[[image:image-20220125171324-4.png]]
83 +[[image:image-20220222153157-4.png]]
83 83  
84 -Once you have some image features selected and at least one brush annotation, ilastik will automatically use your examples to predict what classes the rest of your dataset should be, displaying the results in a "predictions" tab.
85 +Once you have some image features selected and some brush annotation of at least 2 colors, you can check "Live Update" and ilastik will automatically use your examples to predict what classes the rest of your dataset should be, displaying the results in a "predictions" tab.
85 85  
86 -[[image:image-20220125171715-5.png]]
87 +[[image:image-20220222153610-5.png]]
87 87  
89 +
90 +You can keep adding or removing brush strokes to improve your predictions.
91 +
88 88  You can adjust the display settings of the overlay predictions layer as you would in vanilla neuroglancer:
89 89  
90 90  1. right-click the predictions Neuroglancer tab to reveal the "rendering" options
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