Pipeline operations
- 15 Mar 2023
- 1 Minute to read
- Print
- DarkLight
- PDF
Pipeline operations
- Updated on 15 Mar 2023
- 1 Minute to read
- Print
- DarkLight
- PDF
Article summary
Did you find this summary helpful?
Thank you for your feedback
The 'Pipelines' page is available on the left navigation panel at 'Data->Process->Pipelines' as shown below.
The default listing has a list of pre-registered pipelines provided by Data Explorer out-of-the-box and can be identified with the 'Akridata' badge, as shown above.
Copy and customize a pre-registered pipeline
A new pipeline can be created by copying and customizing an existing pipeline. This flow can be used to build a pipeline starting from a pre-registered pipeline as the base.
- On the pipelines page, click the 3 dot icon on the card corresponding to the pipeline to be used as the base.
- Click on the 'Make a copy' option.
- Fill in the pipeline name and description and edit the docker images to override the base pipeline docker images.
- Click on the 'Save Pipeline' button.
Create a new pipeline
- Click on the '+Pipeline' button on the top right of the Pipelines page.
- Fill in the pipeline name, description, and data type for which this pipeline is valid.
- Select the docker images for each pipeline module from the drop-down list. The 'Preprocessor', 'Featurizer' and 'Thumbnail Generator' are mandatory modules to be selected. For the pre-processor, 'AkridataImagePreprocessor' is a passthrough pre-processor that must be selected if there is no specific pre-processing to be executed.
- Click on the 'Save Pipeline' button.
Edit a pipeline
- On the card corresponding to the pipeline to be edited, click on the 'Edit' button.
- On the form presented, edit the fields that are available for editing, like the pipeline name, pipeline description and thumbnail generator docker image.
- Click on 'Save Pipeline'.
Editing pre-processor and featurizer
The pre-processor and featurizer directly impact the features generated for an image/frame, potentially resulting in the incompatibility of features generated before and after pipeline edit operation. Hence these docker images are not allowed for editing. Please make a copy and create a new pipeline if these docker images must be modified.
Delete a pipeline
- On the card corresponding to the pipeline to be deleted, click on the 'Delete' button.
- Confirm the deletion by clicking 'Ok' on the below confirmation prompt.
Deleting pipeline with attached datasets
Deleting a pipeline that has attached datasets will fail. Please detach all datasets and then delete the pipeline.
View pipeline details
- On the card corresponding to the pipeline whose details are required, click on the pipeline name as shown below.
- This shows a details page as below.
Was this article helpful?