Contextualization

Entity Matching

These APIs will return as soon as possible, deferring a blocking wait until the last moment. Nevertheless, they can block for a long time awaiting results.

Fit Entity Matching Model

cognite.client._api.entity_matching.EntityMatchingAPI.fit

Re-fit Entity Matching Model

cognite.client._api.entity_matching.EntityMatchingAPI.refit

Retrieve Entity Matching Models

cognite.client._api.entity_matching.EntityMatchingAPI.retrieve

cognite.client._api.entity_matching.EntityMatchingAPI.retrieve_multiple

cognite.client._api.entity_matching.EntityMatchingAPI.list

Delete Entity Matching Models

cognite.client._api.entity_matching.EntityMatchingAPI.delete

Update Entity Matching Models

cognite.client._api.entity_matching.EntityMatchingAPI.update

Predict Using an Entity Matching Model

cognite.client._api.entity_matching.EntityMatchingAPI.predict

Engineering Diagrams

Detect entities in Engineering Diagrams

cognite.client._api.diagrams.DiagramsAPI.detect

Convert to an interactive SVG where the provided annotations are highlighted

cognite.client._api.diagrams.DiagramsAPI.convert

Vision

The Vision API enable extraction of information from imagery data based on their visual content. For example, you can can extract features such as text, asset tags or industrial objects from images using this service.

Quickstart

Start an asynchronous job to extract information from image files stored in CDF:

from cognite.client import CogniteClient
from cognite.client.data_classes.contextualization import VisionFeature

c = CogniteClient()
extract_job = c.vision.extract(
    features=[VisionFeature.ASSET_TAG_DETECTION, VisionFeature.PEOPLE_DETECTION],
    file_ids=[1, 2],
)

The returned job object, extract_job, can be used to retrieve the status of the job and the prediction results once the job is completed. Wait for job completion and get the parsed results:

extract_job.wait_for_completion()
for item in extract_job.items:
    predictions = item.predictions
    # do something with the predictions

Save the prediction results in CDF as Annotations:

extract_job.save_predictions()

Note

Prediction results are stored in CDF as Annotations using the images.* annotation types. In particular, text detections are stored as images.TextRegion, asset tag detections are stored as images.AssetLink, while other detections are stored as images.ObjectDetection.

Tweaking the parameters of a feature extractor:

from cognite.client.data_classes.contextualization import FeatureParameters, TextDetectionParameters

extract_job = c.vision.extract(
    features=VisionFeature.TEXT_DETECTION,
    file_ids=[1, 2],
    parameters=FeatureParameters(text_detection_parameters=TextDetectionParameters(threshold=0.9))
    # or
    # parameters = {"textDetectionParameters": {"threshold": 0.9}}
)

Extract

cognite.client._api.vision.VisionAPI.extract

Get vision extract job

cognite.client._api.vision.VisionAPI.get_extract_job