Classification¶

class ClassificationPrediction(confidence, label)¶

A single prediction from Classification.

property label¶

The label describing this prediction result.

Type: string

property confidence¶

The confidence of this prediction.

Type: float

class ClassificationResults(predictions, duration, image)¶

All the results of classification from Classification.

Predictions are stored in sorted order, with descending order of confidence.

property duration¶

The duration of the inference in seconds.

Type: float

property predictions¶

The list of predictions.

Type: list of ClassificationPrediction

property image¶

The image the results were processed on.

Image is not available when results are obtained from EyeCloud Cameras.

Type: numpy array – The image in BGR format

class Classification(model_id)¶

Identify the most prominent object in an image.

Typical usage:

classifier = edgeiq.Classification('alwaysai/googlenet')
classifier.load(engine=edgeiq.Engine.DNN)

<get image>
results = classifier.classify_image(image)
for prediction in results.predictions:
    print('Label: {}, confidence: {}'.format(
        prediction.label, prediction.confidence))

Parameters: model_id (string) – The ID of the model you want to use for image classification.

classify_image(image, confidence_level=0.3)¶

Identify the most prominent object in the specified image.

Parameters

image (numpy array of image) – The image to analyze.
confidence_level (float in range [0.0, 1.0]) – The minimum confidence level required to successfully accept a classification.

Returns

ClassificationResults

publish_analytics(results, tag=None)¶

Publish Classification results to the alwaysAI Analytics Service

Parameters

results (ClassificationResults) – The results to publish.
tag (JSON-serializable object) – Additional information to assist in querying and visualizations.

property accelerator¶

The accelerator being used.

Return type: Optional[Accelerator]

property colors¶

The auto-generated colors for the loaded model.

Note: Initialized to None when the model doesn’t have any labels. Note: To update, the new colors list must be same length as the label list.

Return type: List[Tuple[int, int, int]]

property engine¶

The engine being used.

Return type: Optional[Engine]

property labels¶

The labels for the loaded model.

Note: Initialized to None when the model doesn’t have any labels.

Return type: List[str]

load(engine=<Engine.DNN: 'DNN'>, accelerator=<Accelerator.DEFAULT: 'DEFAULT'>)¶

Load the model to an engine and accelerator.

Parameters

engine (Engine) – The engine to load the model to
accelerator (Accelerator) – The accelerator to load the model to

property model_config¶

The configuration of the model that was loaded

Return type: ModelConfig

property model_id¶

The ID of the loaded model.

Return type: str

property model_purpose¶

The purpose of the model being used.

Return type: str