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Create Integration
Download Data
Modify JSON
tabular-data.json
file in the e2e-tabular-data.zip file.tabular-data.json
file and replace <file-path>
with the file path to the data stored in your cloud storage.tabular-data.json
file includes the file path and title for each CSV file. It does NOT include clientMetadata
.Create a Mirrored Dataset
E2E - Tabular Data - Dataset
using the UI. Using mirrored Datasets is a simple way to sync data from folders to Datasets. Mirrored Datasets provide no method of curating or managing your data.If you want to add more data to your Dataset, add more data to the JSON file. Then re-import the JSON file and data automatically gets added to your Dataset and Project.Register/Import Data
tabular-data.json
, from the e2e-tabular-data.zip
, to register/import the data to the mirrored Dataset.genre-options.csv
and platform-options.csv
from the e2e-tabular-data.zip
file.video_game_annotation_X.csv
from the e2e-tabular-data.zip
file.tabular_create_ontology.py
script. You create this.tabular_create_ontology.py
script does the following:
video_game_annotation_X.csv
files.genre-options.csv
.platform-options.csv
.E2E - Tabular Data - Ontology
appears in your Ontology list after running the script.
E2E - Tabular Data - Project
Pre-label
Labelled
tabular_run_agent.py
populates tasks in the AGENT block in your workflow.
Create the following Python scripts. Both scripts must be in the same directory.
tabular_run_agent.py
tabular_utils.py
tabular_run_agent.py
script.
After running the script, tasks that were in the AGENT stage are now in the CONSENSUS - ANNOTATE stage.
E2E - Tabular Data - Ontology
uses text regions, but your annotators and reviewers use drop downs.
In this section, you’ll see the following Collaborators:
Prepare to Label
Team Manager or Project Admin
75
.Set Priority to 75
Annotators
Label Data
Team Manager or Project Admin
Annotators
Review Labels
Team Manager or Project Admin
Review Labels
Export Labels
Project Admin