A way to programmatically set opacity and color of layers?

[azatian]

Hello!

Is there a way to programmatically set the opacity and the color of layers? Is there a value I can programmatically set within the meta data json file that would enable this automatically? Please see screenshot below. The default settings for these two layers is that there is 100 opacity and no color set.

Thank you for your help.

[hotzenklotz]

Yes, you can specify the default values for each layer programmatically. You set dataset.default_view_configuration = LayerViewConfiguration(...). This code snippet contains an example.

For completeness sake, here is how you set this manually.

Keep in mind, the first time you open any dataset and fiddle with these values, webKnossos will save your personal preference. In other words, changing the default values will only go into effect for 1) users opening a dataset for the first time or 2) new datasets.

[azatian]

I see! Is it possible to do this with wkcuber? I have been using wkcuber CLI to convert our TIFF files into wkw then moving them into the appropriate folder on our server where WK is hosted

…

On Mon, Nov 28, 2022, 3:05 PM Tom Herold ***@***.***> wrote: Yes, you can specify the default values for each layer programmatically. You set dataset.default_view_configuration = LayerViewConfiguration(...) <https://docs.webknossos.org/api/webknossos/dataset/dataset.html#Dataset.default_view_configuration>. This code snippet contains an example <https://docs.webknossos.org/webknossos-py/examples/upload_image_data.html> . For completeness sake, here is how you set this manually <https://docs.webknossos.org/webknossos/datasets.html#view-configuration-tab> . Keep in mind, the first time you open any dataset and fiddle with these values, webKnossos will save your personal preference. In other words, changing the default values will only go into effect for 1) users opening a dataset for the first time or 2) new datasets. — Reply to this email directly, view it on GitHub <#827 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ACGLBQS4DB3YM3MN7WHK4J3WKSGV7ANCNFSM6AAAAAASNE7IZ4> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[hotzenklotz]

Is it possible to do this with wkcuber?

No, it is not possible with the wKCuber. You can, however, you use the wK Python Lib to convert a TIFF image stack with Dataset.from_images(...). This is used by the wkCuber under the hood anyway.

[azatian]

Thank you! I have been making some progress on this with the WK Python Lib
Each individual TIFF file has a shape of 160x160x16, but when I add the TIFFs as layers, the width comes out to be 160, the height comes out to be 16, and the depth comes out to be 1. Is there something that I am missing here?

 dataset = wk.Dataset("cutouts/dcvsyn1", voxel_size=(4,4,40))

 img_layer = dataset.add_layer_from_images(images="cutouts/dcvsyn1_source",
                                 layer_name="img", dtype='uint8', channel=0)

 pre_layer = dataset.add_layer_from_images(images="cutouts/dcvsyn1_presyn",
                                             layer_name="presyn", dtype='uint8', channel=0)

 post_layer = dataset.add_layer_from_images(images="cutouts/dcvsyn1_postsyn",
                                             layer_name="postsyn", dtype='uint8', channel=0)

 pre_layer.default_view_configuration = LayerViewConfiguration(
         color=(184, 66, 66), alpha=20)

 post_layer.default_view_configuration = LayerViewConfiguration(
         color=(57, 81, 137), alpha=20)

[azatian]

I think I've somewhat figured out what might the issue be. Dataset.from_images reads the single but multi-page TIFF file differently from add_layer_from_images. Might have to do with Dataset.ConversionLayerMapping? See corresponding json file below.

dataset = wk.Dataset.from_images(input_path="cutouts/dcvsyn1_source",
                                output_path="cutouts/dcvsyn1",
                                voxel_size=(4,4,40),
                                name="dcvsyn1")
   
dataset.layers['vol.tiff'].name = "img"
    
pre_layer = dataset.add_layer_from_images(images="cutouts/dcvsyn1_presyn",
                                               layer_name="presyn", dtype='uint8', channel=1)

{
    "id": {
        "name": "dcvsyn1",
        "team": ""
    },
    "scale": [
        4.0,
        4.0,
        40.0
    ],
    "dataLayers": [
        {
            "name": "img",
            "category": "color",
            "boundingBox": {
                "topLeft": [
                    0,
                    0,
                    0
                ],
                "width": 160,
                "height": 160,
                "depth": 16
            },
            "elementClass": "uint8",
            "dataFormat": "wkw",
            "numChannels": 1,
            "wkwResolutions": [
                {
                    "cubeLength": 1024,
                    "resolution": [
                        1,
                        1,
                        1
                    ]
                }
            ]
        },
        {
            "name": "presyn",
            "category": "color",
            "boundingBox": {
                "topLeft": [
                    0,
                    0,
                    0
                ],
                "width": 160,
                "height": 16,
                "depth": 1
            },
            "elementClass": "uint8",
            "dataFormat": "wkw",
            "numChannels": 1,
            "wkwResolutions": [
                {
                    "cubeLength": 1024,
                    "resolution": [
                        1,
                        1,
                        1
                    ]
                }
            ]
        }
    ]
}

[jstriebel]

@azatian Thank you for reporting this bug! 🐞

I think I can reproduce the problem locally and will work on a fix. In the meantime it might work for you if you use the full path to the file in add_layer_from_images:

dataset.add_layer_from_images(images="cutouts/dcvsyn1_presyn/name_of_your.tiff", …)

I'll write back when the fix is deployed, then it should work with the folder-name as well.

[azatian]

Hello! I see! I shall try that. I was able to get around it by doing making individual datasets per layer but tying them with the same output path:

dataset = wk.Dataset.from_images(input_path="cutouts/dcvsyn1_source",
                                output_path="cutouts/dcvsyn1",
                                voxel_size=(4,4,40),
                                name="dcvsyn1")

dataset.layers['vol.tiff'].name = "img"
dataset_pre = wk.Dataset.from_images(input_path="cutouts/dcvsyn1_presyn",
                                output_path="cutouts/dcvsyn1",
                                voxel_size=(4,4,40),
                                name="dcvsyn1")
    

dataset_pre.layers['presyn.tiff'].default_view_configuration = LayerViewConfiguration(color=(184, 66, 66), alpha=20)
dataset_pre.layers['presyn.tiff'].name = "presyn"

dataset_post = wk.Dataset.from_images(input_path="cutouts/dcvsyn1_postsyn",
                                output_path="cutouts/dcvsyn1",
                                voxel_size=(4,4,40),
                                name="dcvsyn1")

 dataset_post.layers['postsyn.tiff'].default_view_configuration = LayerViewConfiguration(color=(57, 81, 137), alpha=20)
 dataset_post.layers['postsyn.tiff'].name = "postsyn"

[azatian]

Here is the associated json file, where the input shapes are now correct for all layers:

{
    "id": {
        "name": "dcvsyn1",
        "team": ""
    },
    "scale": [
        4.0,
        4.0,
        40.0
    ],
    "dataLayers": [
        {
            "name": "img",
            "category": "color",
            "boundingBox": {
                "topLeft": [
                    0,
                    0,
                    0
                ],
                "width": 160,
                "height": 160,
                "depth": 16
            },
            "elementClass": "uint8",
            "dataFormat": "wkw",
            "numChannels": 1,
            "wkwResolutions": [
                {
                    "cubeLength": 1024,
                    "resolution": [
                        1,
                        1,
                        1
                    ]
                }
            ]
        },
        {
            "name": "presyn",
            "category": "color",
            "boundingBox": {
                "topLeft": [
                    0,
                    0,
                    0
                ],
                "width": 160,
                "height": 160,
                "depth": 16
            },
            "elementClass": "uint8",
            "dataFormat": "wkw",
            "numChannels": 1,
            "defaultViewConfiguration": {
                "color": [
                    184,
                    66,
                    66
                ],
                "alpha": 20.0
            },
            "wkwResolutions": [
                {
                    "cubeLength": 1024,
                    "resolution": [
                        1,
                        1,
                        1
                    ]
                }
            ]
        },
        {
            "name": "postsyn",
            "category": "color",
            "boundingBox": {
                "topLeft": [
                    0,
                    0,
                    0
                ],
                "width": 160,
                "height": 160,
                "depth": 16
            },
            "elementClass": "uint8",
            "dataFormat": "wkw",
            "numChannels": 1,
            "defaultViewConfiguration": {
                "color": [
                    57,
                    81,
                    137
                ],
                "alpha": 20
            },
            "wkwResolutions": [
                {
                    "cubeLength": 1024,
                    "resolution": [
                        1,
                        1,
                        1
                    ]
                }
            ]
        }
    ]
}

[hotzenklotz]

@jstriebel Has this issue been resolved with PR #829? Perhaps, @azatian can re-test with your new release.

[jstriebel]

I was able to get around it by doing making individual datasets per layer but tying them with the same output path:

Great that you found a workaround, @azatian! We just released a version with a fix for the problem, version 0.10.26. Could you re-try your original code you posted above with the new version? That would be great to verify that this is indeed fixed for you.

[jstriebel]

Closing this for now. @azatian please let us know if something is unresolved.