Multi-view images
Last updated
Last updated
Multi-view mode is a feature that allows you to view and annotate multiple images simultaneously. It is especially useful when you need to label objects from different perspectives, 3D reconstruction images, Autonomous vehicle camera views or depth estimation task images. Labeling in multi-view mode can significantly increase the speed of the labeling process (for example, you don't need to switch between images and select a desired class to label the same object)
Just organize images into groups and drop them to the import. The app will do the rest: it will detect groups, tag images, and activate grouping and multi-view modes in the project settings.
Note: To use the multi-view import feature, you need to create a project with the Multi-view image annotation setting enabled. You can also enable this setting in the project settings after the import. Here is an illustration of how to upload multi-view images:
Supported image formats: .jpg, .jpeg, .mpo, .bmp, .png, .webp, .tiff, .tif, .jfif, .avif, .heic, and .heif
With annotations: Yes
Annotation types: Tags in Supervisely format
Grouped by: Folders (corresponding tags will be assigned to images)\
All images in groups in the created project will be tagged
Images Grouping option will be turned on by default in the created project
Images will be grouped by tag's value
Tag value is defined by the group directory name
Works with .nrrd image format (2D only)
1. Prepare structure:
Archive zip, tar, tar.xz, tar.gz
Folder
Structure explained:
An archive must contain only 1 project directory.
Inside the project directory must be 1 dataset directory.
Group directories must be populated with images and placed inside the dataset directory. All images inside the group will be tagged with folder name value.
All images in the root dataset directory will be uploaded as regular images and will not be tagged.
We prepared sample datasets for you to try the import process:
images: download ⬇️
NRRD: download ⬇️
To display single images switch off Images Grouping setting.
If you want to disable images grouping for the whole project, go to Project → Settings → Visuals and uncheck
Windowing tool is available when working with .nrrd files. It helps to filter pixels to see bones, air, liquids etc.
Images view synchronization
Automate processes with multi-view images using Supervisely Python SDK.
You can learn more about it in our Developer Portal, but here we'll just give you a quick examples of how you can get started with multi-view images.
The following code snippets demonstrate how you can upload your multi-view images with just a few lines of code.
In the example above we uploaded two groups of multi-view images. Before or after uploading images, we also need to enable image grouping in the project settings.\
Available starting from version v6.73.236 of the Supervisely Python SDK.
If you already have images in your project and you want to group them for multi-view, you can group them by your own logic. By default, images will be grouped by the value of the multiview tag. You can change the tag name by passing the multiview_tag_name argument.
Here is an example of how you can do it with just a few lines of code.
If the tag does not exist, it will be created automatically.
If multi-view mode is not enabled in the project settings, it will be enabled automatically.
Let's consider a more complex example. For instance, you have a project with several datasets containing images and you want to group them by dataset name. Here is an example of how you can do it.
We recommend grouping images in batches of 6-12 images (depending on the size of your display).
Synchronization OFF
Synchronization ON
