Add image captions to documentation

docs/automation/ai_segmentation.md

@@ -17,20 +17,27 @@ As a first trial, WEBKNOSSOS includes neuron segmentation. This analysis is desi
 You can launch the AI analysis dialog using the `AI Analysis` button in the toolbar at the top. Use the `Start AI neuron segmentation` button in the dialog to start the analysis.
 
 ![Neuron segmentations can be launched from the tool bar.](../images/process_dataset.jpg)
+/// caption
+Neuron segmentations can be launched from the tool bar.
+///
 
 Computation time for this analysis depends directly on the size of your dataset. 
 Expect a few hours for medium-sized volumetric EM datasets. 
 The finished analysis will be available as a new dataset from your dashboard. You can monitor the status and progress of the analysis job from the [`Processing Jobs` page](./jobs.md) or wait for the email notification.
 
 ![Starting a new neuron segmentation.](../images/neuron_segmentation_start.jpeg)
+/// caption
+Starting a new neuron segmentation.
+///
 ![Monitor the segmentation progress from the Jobs page.](../images/nuclei_segmentation_job.jpeg)
+/// caption
+Monitor the segmentation progress from the Jobs page.
+///
 
 ## Mitochondria detection
 Similarly to the neuron segmentation, you can now start a mitochondria detection in WEBKNOSSOS. In the AI analysis dialog, choose `Mitochondria detection`, select a bounding box, and go to `Processing Jobs` to look at the result. 
 
 ## Custom Analysis
 You'll soon be able to train custom classifiers directly in WEBKNOSSOS. [Contact us](mailto:[email protected]) for an invite to join the beta program.
 
-If you are interested in specialized, automated analysis, image segmentation, object detection etc. then feel free to [contact us](mailto:[email protected]). The WEBKNOSSOS development teams offers [commercial analysis services](https://webknossos.org/services/automated-segmentation) for that. 
-
-
+If you are interested in specialized, automated analysis, image segmentation, object detection etc. then feel free to [contact us](mailto:[email protected]). The WEBKNOSSOS development teams offers [commercial analysis services](https://webknossos.org/services/automated-segmentation) for that.

docs/automation/alignment.md

@@ -5,4 +5,4 @@ Simply upload the dataset, open it and select the "Alignment" tab in the AI Anal
 
 You can even annotate landmarks with the skeleton tool and use that to let WEBKNOSSOS align the dataset. Often these landmarks are not necessary, but for particularly hard to align sections, they can be quite useful. When manual landmarks are used, they don't need to cover the entire dataset.
 
-For multi-tile image stacks, please refer to our [Alignment services](https://webknossos.org/services/alignment).
+For multi-tile image stacks, please refer to our [Alignment services](https://webknossos.org/services/alignment).

docs/automation/animations.md

@@ -44,4 +44,4 @@ You can choose between two resolutions for your animation video:
 ### Layer & Bounding Box
 
 - **Layer:** Select the data layer to be used for the animation.
-- **Bounding Box:** Choose the bounding box for the animation. By default, the entire layer is selected. You can create custom bounding boxes using the [bounding box tool](../ui/toolbar.md#measurement-tools).
+- **Bounding Box:** Choose the bounding box for the animation. By default, the entire layer is selected. You can create custom bounding boxes using the [bounding box tool](../ui/toolbar.md#measurement-tools).

docs/automation/index.md

@@ -2,4 +2,4 @@
 
 WEBKNOSSOS integrates several automated workflows that run in the background. The main workflows include [AI segmentation](ai_segmentation.md), [image alignment](alignment.md), and [exporting 3D animations](animations.md). More workflows are detailed on the [Jobs](jobs.md) page.
 
-![youtube-video](https://www.youtube.com/embed/8ijhmiJs3qY)
+![youtube-video](https://www.youtube.com/embed/8ijhmiJs3qY)

docs/automation/jobs.md

@@ -29,5 +29,8 @@ Depending on the job workflow you may:
 - download the data, e.g., [Tiff export](../data/export_ui.md)
 
 ![Overview of the Jobs page](../images/jobs.jpeg)
+/// caption
+Overview of the Jobs page
+///
 
-We constantly monitor job executions. In rare cases, jobs can fail, and we aim to re-run them as quickly as possible. In case you run into any trouble please [contact us](mailto:[email protected]).
+We constantly monitor job executions. In rare cases, jobs can fail, and we aim to re-run them as quickly as possible. In case you run into any trouble, please [contact us](mailto:[email protected]).

docs/connectome_viewer.md

@@ -12,6 +12,9 @@ Synapse locations, types, and partners have to be pre-computed outside of WEBKNO
 - Filtering by synapse type or direction 
 
 ![The Synapse and Connectome viewer displays the incoming and outgoing synaptic connections for a selected neuron.](./images/connectome_viewer.jpeg)
+/// caption
+The Synapse and Connectome viewer displays the incoming and outgoing synaptic connections for a selected neuron.
+///
 
 ## Getting started with the Synapse & Connectome Viewer
 
@@ -36,4 +39,4 @@ my_dataset                          # Dataset root
 
 
 ## Connectome File Format
-The connectome file format is under active development and experiences frequent changes. [Please reach out to us for the latest file format spec and configuration help](mailto://[email protected]).
+The connectome file format is under active development and experiences frequent changes. [Please reach out to us for the latest file format spec and configuration help](mailto://[email protected]).

docs/dashboard/annotations.md

@@ -7,10 +7,16 @@ You can also add custom tags to annotations to organize and group them. Click on
 Each annotation can be renamed to reflect its content.
 
 ![Manage and resume your skeleton and volume annotations.](../images/dashboard_annotations.png)
-![Annotations can archived to declutter your dashboard.](../images/dashboard_archive.png)
+/// caption
+Manage and resume your skeleton and volume annotations.
+///
+![Annotations can be archived to declutter your dashboard.](../images/dashboard_archive.png)
+/// caption
+Annotations can be archived to declutter your dashboard.
+///
 
 ## Shared Annotations
 
 The annotations tab also shows all annotations that were shared by other collaborators of your organization. Only annotations shared through the "Team Sharing" mechanic will be listed provided your user account is part of the respective team. Read more about sharing your own annotations in the [Sharing guide](../sharing/annotation_sharing.md).
 
-You can view the linked annotations (read-only) or copy them to your account for modification.
+You can view the linked annotations (read-only) or copy them to your account for modification.

docs/dashboard/datasets.md

@@ -11,4 +11,7 @@ If you are [an Admin, a Dataset Manager or a Team Manager](../users/access_right
 
 Read more about the organization of datasets [here](../datasets/organization.md).
 
-![Dashboard for Team Managers or Admins with access to dataset settings and additional administration actions.](../images/screenshot_DS_management.png)
+![Dashboard for Team Managers or Admins with access to dataset settings and additional administration actions.](../images/screenshot_DS_management.png)
+/// caption
+Dashboard for Team Managers or Admins with access to dataset settings and additional administration actions.
+///

docs/dashboard/featured_publications.md

@@ -5,3 +5,6 @@ This screen lists a number of featured public community datasets and their respe
 [Contact us](mailto:[email protected]) if you would like your data and publication to be featured here as well.
 
 ![The list of featured community datasets.](../images/dashboard_featured_publications.png)
+/// caption
+The list of featured community datasets.
+///

docs/dashboard/index.md

@@ -8,10 +8,4 @@ Check out these sections to become familiar with the WEBKNOSSOS dashboard:
 - [Dataset dashboard](./datasets.md)
 - [Annotation dashboard](./annotations.md)
 - [Tasks dashboard](tasks.md)
-- [Featured publications dashboard](featured_publications.md)
-
-
-
-
-
-
+- [Featured publications dashboard](featured_publications.md)

docs/dashboard/tasks.md

@@ -6,4 +6,7 @@ Tasks are small annotation work assignments that are automatically distributed t
 On the Task screen, users can request new tasks, continue to work on existing tasks, and finish tasks. These tasks are assigned based on a user's experience level, project priority, and task availability.
 Read more about the tasks feature in the [Tasks and Projects guide](../tasks_projects/index.md).
 
-![Tasks can be distributed to users. Task can include rich instructions.](../images/dashboard_tasks.png)
+![Tasks can be distributed to users. Tasks can include rich instructions.](../images/dashboard_tasks.png)
+/// caption
+Tasks can be distributed to users. Tasks can include rich instructions.
+///

docs/data/concepts.md

@@ -9,6 +9,9 @@ Each cube contains multiple *buckets* of 32^3 voxel size.
 This is the unit in which the data is streamed to a user's browser.
 
 ![Datasets, Cubes, and Buckets](../images/cubes-and-buckets.jpeg)
+/// caption
+The relationship between datasets, cubes, and buckets.
+///
 
 ## Layers
 
@@ -20,6 +23,9 @@ Additionally, there may be one or more `segmentation` layers that hold manually
 A WEBKNOSSOS dataset can contain several `color` and `segmentation` layers which can be rendered individually or overlaid on top of each other. The maximum number of visible layers depends on your GPU hardware - typically 16 layers.
 
 ![Color and Segmentation Layers](../images/datalayers.jpeg)
+/// caption
+Color layers contain the microscopy data and segmentation layers contain (volume) annotations or masks.
+///
 
 ## Magnification Steps and Downsampling
 
@@ -31,6 +37,9 @@ Downsampling is done in power-of-two steps: `1, 2, 4, 8, 16, 32, 64, …`
 WEBKNOSSOS also supports non-uniform (anisotropic) downsampling. For example, `[2, 2, 1]` is downsampled in the `x` and `y` dimensions, but not in `z`.
 
 ![Downsampling the data to improve zooming](../images/downsampling.jpeg)
+/// caption
+Downsampling the data to improve zooming
+///
 
 
 ## Segmentation
@@ -194,4 +203,4 @@ my_dataset                      # Dataset root
 │  │  ├─ different_mapping.hdf5 # one mapping file per pre-computed mapping strategy
 ```
 
-Note that JSON mappings are deprecated and support will be removed in a future version.
+Note that JSON mappings are deprecated and support will be removed in a future version.

docs/data/export_python.md

@@ -2,4 +2,4 @@
 
 The [WEBKNOSSOS Python library](https://docs.webknossos.org/webknossos-py/) makes it very easy to download/upload any of your organization's datasets, and annotations. For detailed info, please refer to the `webknossos-libs` [documentation website for guides and tutorials](https://docs.webknossos.org/webknossos-py/).
 
-There are also quick start instructions for Python download available directly from the [WEBKNOSSOS UI](./export_ui.md).
+There are also quick start instructions for Python download available directly from the [WEBKNOSSOS UI](./export_ui.md).

docs/data/export_ui.md

@@ -13,4 +13,7 @@ To access the download panel:
 2. Select `Download` entry
 3. Select the desired data for download or export 
 
-![The "Download" dialog for exporting and downloading annotations and dataset layers. WebKnossos offers downloads as Tif stacks, the native WEBKNOSSOS file formats, and through the Python library.](../images/download_dialog.gif)
+![The "Download" dialog for exporting and downloading annotations and dataset layers. WEBKNOSSOS offers downloads as Tiff stacks, the native WEBKNOSSOS file formats, and through the Python library.](../images/download_dialog.gif)
+/// caption
+The "Download" dialog for exporting and downloading annotations and dataset layers. WEBKNOSSOS offers downloads as Tiff stacks, the native WEBKNOSSOS file formats, and through the Python library.
+///

docs/data/image_stacks.md

@@ -108,4 +108,4 @@ Read the full example in the WEBKNOSSOS [Python library documentation](https://d
 
 ---
 
-[Please contact us](mailto:[email protected]) or [write a post in our support forum](https://forum.image.sc/tag/webknossos), if you have any issues with converting your datasets.
+[Please contact us](mailto:[email protected]) or [write a post in our support forum](https://forum.image.sc/tag/webknossos), if you have any issues with converting your datasets.

docs/data/index.md

@@ -14,4 +14,4 @@ The Zarr3 format is used for all internal voxel data representations - both for
 
 Any dataset uploaded to webknossos.org will automatically be converted to Zarr3 on upload - given its source file format is supported by WEBKNOSSOS. Alternatively, you can manually convert your datasets using the [WEBKNOSSOS CLI tool](https://docs.webknossos.org/cli/) or use a custom script based on the [WEBKNOSSOS Python library](https://docs.webknossos.org/webknossos-py/).
 
-Read more about uploading and configuring datasets on the [datasets page](../datasets/settings.md).
+Read more about uploading and configuring datasets on the [datasets page](../datasets/settings.md).

docs/data/n5.md

@@ -35,4 +35,4 @@ For details see the [N5 spec](https://github.com/saalfeldlab/n5).
 ## Performance Considerations
 To get the best streaming performance for N5 datasets consider the following settings.
 
-- Use chunk sizes of 32 - 128 voxels^3
+- Use chunk sizes of 32 - 128 voxels^3

docs/data/neuroglancer_precomputed.md

@@ -41,4 +41,4 @@ For details see the [Neuroglancer spec](https://github.com/google/neuroglancer/t
 To get the best streaming performance for Neuroglancer Precomputed datasets consider the following settings.
 
 - Use chunk sizes of 32 - 128 voxels^3
-- Enable sharding
+- Enable sharding

docs/data/streaming.md

@@ -27,4 +27,4 @@ Any other WEBKNOSSOS feature, e.g., annotations, and access rights, will be stor
 
 Note that data streaming may incur costs and count against any usage limits or minutes as defined by these third-party services. Check with the service provider or dataset owner.
 
-![youtube-video](https://www.youtube.com/embed/43dvqqAg_MQ)
+![youtube-video](https://www.youtube.com/embed/43dvqqAg_MQ)

docs/data/upload_python.md

@@ -1,2 +1,2 @@
 ### Uploading through Python
-For those wishing to automate dataset upload or to do it programmatically, check out the WEBKNOSSOS [Python library](https://docs.webknossos.org/webknossos-py/). You can create, manage and upload datasets with the Python lib. 
+For those wishing to automate dataset upload or to do it programmatically, check out the WEBKNOSSOS [Python library](https://docs.webknossos.org/webknossos-py/). You can create, manage and upload datasets with the Python library.

docs/data/upload_ui.md

@@ -52,4 +52,4 @@ We support a variety of data types for the uploaded data. To make sure that your
 |    float   |       ✓     |        ✗                   |
 |    double  |       ✗     |        ✗                   |
 
-Once the data is uploaded (and potentially converted), you can further configure a dataset's [Settings](../datasets/settings.md) and double-check layer properties, fine tune access rights & permissions, or set default values for rendering.
+Once the data is uploaded (and potentially converted), you can further configure a dataset's [Settings](../datasets/settings.md) and double-check layer properties, fine tune access rights & permissions, or set default values for rendering.

docs/data/wkw.md

@@ -73,4 +73,4 @@ volumetracing.zip # A ZIP file containing the volume annotation
 └─ volumetracing.nml # Annotation metadata NML file
 ```
 
-After unzipping the archives, the WKW files can be read or modified with the [WEBKNOSSOS Python library](https://docs.webknossos.org/webknossos-py/examples/load_annotation_from_file.html).
+After unzipping the archives, the WKW files can be read or modified with the [WEBKNOSSOS Python library](https://docs.webknossos.org/webknossos-py/examples/load_annotation_from_file.html).

docs/data/zarr.md

@@ -141,7 +141,7 @@ You can use the free [WEBKNOSSOS Python library](https://docs.webknossos.org/web
 ```python
 import webknossos as wk
 
-def main() -> None:
+def main() -> None: 
     """Convert a folder of image files to a WEBKNOSSOS dataset."""
     dataset = wk.Dataset.from_images(
         input_path=INPUT_DIR,
@@ -173,5 +173,4 @@ To get the best streaming performance for Zarr datasets consider the following s
 
 - Use chunk sizes of 32 - 128 voxels^3
 - Enable sharding (only available in Zarr 3+)
-- Use 3D downsampling
-
+- Use 3D downsampling

docs/data/zarr_stream.md

@@ -10,9 +10,11 @@ To access and share a dataset through Zarr streaming, follow these steps:
 1. Click on the overflow menu (dropdown), next to the `Save` button in the WEBKNOSSOS navbar
 2. Select `Zarr Links` entry
 3. Click `Create Zarr Link` to make the resource available through the Zarr streaming interface. Set the `Expiration Date` as required. The default duration is 1 month into the future.
-4. Click on the little copy button (clipboard icon) to copy the Zarr web link. Due to the nature of the Zarr spec, if you need to individually copy a URL for each WEBKNOSSOS layer.
+4. Click on the little copy button (clipboard icon) to copy the Zarr web link. Due to the nature of the Zarr spec, you need to individually copy the URL for each WEBKNOSSOS layer.
 
 ![The Zarr Link dialog for sharing a dataset/annotation as a Zarr source for streaming to third-party services.](../images/zarr_links.jpeg)
+/// caption
+The Zarr Link dialog for sharing a dataset/annotation as a Zarr source for streaming to third-party services.
+///
 
-A unique aspect of WEBKNOSSOS is private Zarr links. Any annotation shared through Zarr generates a web link containing a unique access token for authentication such that only allowed users and collaborators may access this data. This is akin to WEBKNOSSOS ability to [privately share annotations through web URLs](../sharing/annotation_sharing.md). Zarr links can be revoked/deleted at any time (or time-limited by default) to retain control over your data.
-
+A unique aspect of WEBKNOSSOS is private Zarr links. Any annotation shared through Zarr generates a web link containing a unique access token for authentication such that only allowed users and collaborators may access this data. This is akin to WEBKNOSSOS ability to [privately share annotations through web URLs](../sharing/annotation_sharing.md). Zarr links can be revoked/deleted at any time (or time-limited by default) to retain control over your data.

docs/datasets/composing.md

@@ -11,5 +11,4 @@ There are three different ways to compose a new dataset:
 
 See the "Compose from existing datasets" tab in the "Add Dataset" screen for more details.
 
-![youtube-video](https://www.youtube.com/embed/BV6Hw9v3pao)
-
+![youtube-video](https://www.youtube.com/embed/BV6Hw9v3pao)

docs/datasets/external_storage.md

@@ -7,4 +7,4 @@ This may be useful when dealing with large datasets that should remain in your d
 scalable minds also offers a dataset alignment tool called *Voxelytics Align*.
 [Learn more.](https://scalableminds.com/voxelytics-align)
 
-![youtube-video](https://www.youtube.com/embed/yYauIHZcI_4)
+![youtube-video](https://www.youtube.com/embed/yYauIHZcI_4)

docs/datasets/index.md

@@ -35,4 +35,4 @@ For convenience and testing, we provide a list of sample datasets for WEBKNOSSOS
   [https://static.webknossos.org/data/MPRAGE_250um.zip](https://static.webknossos.org/data/MPRAGE_250um.zip)  
   T1-weighted in vivo human whole brain MRI dataset with an ultra-fine isotropic resolution of 250 μm.
   F Lüsebrink, A Sciarra, H Mattern, R Yakupov, O Speck.  
-  Scientific Data. 14 March 2017. [https://doi.org/10.1038/sdata.2017.32](https://doi.org/10.1038/sdata.2017.32)
+  Scientific Data. 14 March 2017. [https://doi.org/10.1038/sdata.2017.32](https://doi.org/10.1038/sdata.2017.32)