Last modified by puchades on 2022/09/30 16:01
From version 39.1
edited by tomazvieira
on 2022/09/11 11:59
Change comment: Uploaded new attachment "webilastik_click_and_drag.png", version {1}
To version 49.1
edited by tomazvieira
on 2022/09/11 16:35
Change comment: Uploaded new attachment "image-20220911163504-5.png", version {1}

Summary

Details

Page properties
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10 10  (% class="wikigeneratedid" %)
11 11  Webilastik is a web application that can be accessed on [[https:~~/~~/app.ilastik.org>>https://app.ilastik.org]]. We suggest using it via the Chrome (or Chromium) web browser for now, since most of the testing has been done in this browser and subtle differences between browsers might cause unexpected behavior in the application.
12 12  
13 -=== Opening a sample Dataset ===
13 +(% class="wikigeneratedid" %)
14 +You can find the webilastik application at [[https:~~/~~/app.ilastik.org/>>url:https://app.ilastik.org/]]. You can also go directly to the [[application page>>https://app.ilastik.org/public/nehuba/index.html#!%7B%22layout%22:%22xy%22%7D]].
14 14  
15 -Go to [[https:~~/~~/app.ilastik.org/>>https://app.ilastik.org/]] and load a [[Neuroglancer Precomputed Chunks dataset>>https://github.com/google/neuroglancer/tree/master/src/neuroglancer/datasource/precomputed]]. You can e.g. use a sample data set that is already in the server by pasting the following URL into Neuroglancer's prompt:
16 +Webilastik is an overlay on top of other data viewers. In particular, this implementation uses [[Neuroglancer>>https://github.com/google/neuroglancer]] as an underlying data viewer, so if you're familiar with its controls you can still use them when using webilastik.
16 16  
18 +=== Moving the controls window ===
19 +
20 +You can move the webilastik controls around the screen by clicking and dragging on the header:
21 +
22 +[[image:webilastik_click_and_drag.png]]
23 +
24 +
25 +=== Opening a Dataset ===
26 +
27 +Like in vanilla Neuroglancer, you add datasets to the viewer by clicking the "+" button at the top of the viewer:
28 +
29 +[[image:webilastik_click_plus_sign_in_neuroglancer.png||height="200"]]
30 +
31 +
32 +You should be presented with a popup prompt where you can type in the URL of a dataset you want to view, in the format typically used by Neuroglancer. There are a few sample datasets hosted in webilastik:
33 +
34 +precomputed:~/~/https:~/~/app.ilastik.org/public/images/mouse1.precomputed
35 +
36 +precomputed:~/~/https:~/~/app.ilastik.org/public/images/mouse2.precomputed
37 +
38 +precomputed:~/~/https:~/~/app.ilastik.org/public/images/mouse3.precomputed
39 +
17 17  precomputed:~/~/https:~/~/app.ilastik.org/public/images/c_cells_2.precomputed
18 18  
42 +precomputed:~/~/https:~/~/app.ilastik.org/public/images/c_cells_3.precomputed
43 +
44 +
45 +After you type or paste the URL into the "Source" field, neuroglancer should recognize the shape and number of channels in the image. You can the click "Add Layer" to open the dataset in the viewer.
46 +
19 19  [[image:image-20220125164204-2.png]]
20 20  
21 21  
22 22  === Opening a Dataset from the data-proxy ===
23 23  
24 -You can also load Neuroglancer Precomputed Chunks data from the data-proxy; The URLs for this kind of data follow the following scheme:
25 -\\##precomputed:~/~/https:~/~/data-proxy.ebrains.eu/api/buckets/(% style="background-color:#3498db; color:#ffffff" %)my-bucket-name(% style="background-color:#9b59b6; color:#ffffff" %)/path/inside/your/bucket(%%)##
52 +You can also load Neuroglancer Precomputed Chunks data from the data-proxy (e.g. the [[ana-workshop-event bucket>>https://wiki.ebrains.eu/bin/view/Collabs/ana-workshop-event/Bucket]]); The URLs for this kind of data follow the following scheme:
53 +\\##precomputed:~/~/https:~/~/data-proxy.ebrains.eu/api/v1/buckets/(% style="background-color:#3498db; color:#ffffff" %)my-bucket-name(% style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255)" %)/(% style="background-color:#9b59b6; color:#ffffff" %)path/inside/your/bucket(%%)##
26 26  
27 -So, for example, to load the sample data inside the (% style="background-color:#3498db; color:#ffffff" %)quint-demo(%%) bucket, under the path (% style="background-color:#9b59b6; color:#ffffff" %)tg-ArcSwe_mice_precomputed/hbp-00138_122_381_423_s001.precomputed(% style="color:#000000" %) (%%) like in the example below:
55 +where (% style="background-color:#9b59b6; color:#ffffff" %)path/inside/your/bucket(%%)  should be the path to the folder containing the dataset "info" file.
28 28  
29 29  
30 -[[image:image-20220128142757-1.png]]
58 +So, for example, to load the sample data inside the (% style="background-color:#3498db; color:#ffffff" %)ana-workshop-event(%%) bucket, under the path (% style="background-color:#9b59b6; color:#ffffff" %)tg-ArcSwe_mice_precomputed/hbp-00138_122_381_423_s001.precomputed(% style="color:#000000" %) (%%) like in the example below:
31 31  
32 -=== ===
60 +(% style="display:none" %) (%%)
33 33  
62 +[[image:webilastik_bucket_paths.png]]
63 +
64 +=== ===
65 +
34 34  you would type a URL like this:
35 35  
36 36  
37 -##precomputed:~/~/https:~/~/data-proxy.ebrains.eu/api/buckets/(% style="background-color:#3498db; color:#ffffff" %)quint-demo(%%)/(% style="background-color:#9b59b6; color:#ffffff" %)tg-ArcSwe_mice_precomputed/hbp-00138_122_381_423_s001.precomputed(%%)##
69 +{{{precomputed://https://data-proxy.ebrains.eu/api/v1/buckets/ana-workshop-event/tg-ArcSwe_mice_precomputed/hbp-00138_122_381_423_s001.precomputed}}}
38 38  
39 39  this scheme is the same whether you're loading data into the Neuroglancer viewer or specifying an input URL in the export applet.
40 40  
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48 48  
49 49  [[image:image-20220125164557-4.png]]
50 50  
83 +You can also click the
51 51  
52 52  ==== A Note on Neuroglancer and 2D data ====
53 53  
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57 57  
58 58  [[image:image-20220222161022-1.png]]
59 59  
93 +(% class="wikigeneratedid" %)
94 +Alternatively, once you have a compute session running you can also click the "Reset" button in the lower-right corner of the viewer to move the viewer back to the center of your datasets:
95 +
96 +(% class="wikigeneratedid" %)
97 +[[image:webilastik_click_recenter_button.png]]
98 +
99 +== Allocating a Compute Session ==
100 +
101 +Normal ilastik operation can be computationally intensive, requiring dedicated compute resources to be allocated to every user working with it.
102 +
103 +The "Session Management" widget allows you to request a compute session where webilastik will run; Select a session duration and click 'Create' to create a new compute session. Eventually the compute session will be allocated, opening up the other workflow widgets.
104 +
105 +Don't forget to close your compute session by clicking the "Close Session" button once you're done to prevent wasting your quota in the HPC. If you have a long running job, though, you can just leave the session and rejoin it later by pasting its session ID in the "Session Id" field of the "Session Management" widget and clicking "rejoin Session".
106 +
60 60  == Training the Pixel Classifier ==
61 61  
62 62  === Selecting Image Features ===
63 63  
64 -Pixel Classification uses different characteristics ("features") of your image to determine which class each pixel should belong to. These take into account, for example, color and texture of each pixel as well as that of the neighboring pixels. Each one of this characteristics requires some computational power, which is why you can select only the ones that are sensible for your particular dataset.
111 +Pixel Classification uses different characteristics ("features") of each pixel from your image to determine which class that pixel should belong to. These take into account, for example, color and texture of each pixel as well as that of the neighboring pixels. Each one of this characteristics requires some computational power, which is why you can select only the ones that are sensible for your particular dataset.
65 65  
66 -Use the checkboxes in the applet "Select Image Features" applet to select some image features and their corresponding sigma (which determines the radius around the pixel that will be considered when computing that feature).
113 +Use the checkboxes in the applet "Select Image Features" applet to select some image features and their corresponding sigma. The higher the sigma, the bigger the vicinity considered when computing values for each pixel, and the bigger its influence over the final value of that feature. Higher sigmas also require more computations to be done and can increase the time required to do predictions.
67 67  
68 68  You can read more about image features in [[ilastik's documentation.>>https://www.ilastik.org/documentation/pixelclassification/pixelclassification\]]
69 69  
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73 73  
74 74  === Labeling the image ===
75 75  
76 -In order to classify the pixels of an image into different classes (e.g.: 'foreground' and 'background') ilastik needs you to provide it with samples of each class.
123 +In order to classify the pixels of an image into different classes (e.g.: 'foreground' and 'background') ilastik needs you to provide it with examples of each class.
77 77  
78 -To do so, first select a particular resolution of your dataset (your viewer might interpolate between multiple scales of the dataset, but ilastik operates on a single resolution):
79 79  
80 -[[image:image-20220125165642-1.png]]
126 +==== Picking an Image Resolution (for multi-resolution images only) ====
81 81  
128 +If your data has multiple resolutions (**not the case in any of the sample datasets**), you'll have to pick one of them in the "Training" widget. Neuroglancer interpolates between multiple scales of the dataset, but ilastik operates on a single resolution:
129 +
130 +[[image:image-20220911155827-1.png]]
131 +
82 82  Once you've selected a resolution to train on, you should see a new "training" tab at the top of the viewer:
83 83  
84 84  [[image:image-20220125165832-2.png]]
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87 87  
88 88  [[image:image-20220222151117-1.png]]
89 89  
140 +==== ====
90 90  
91 -The status display in this applet will show "training on [datasource url]" when you're in training mode.
142 +==== Painting Labels ====
92 92  
144 +The status display in the "Training" applet will show "training on [datasource url]" when it's ready to start painting.
145 +
93 93  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.
94 94  
95 95  [[image:image-20220222153157-4.png]]
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