Classification information produced by an image analysis request.


class VNClassificationObservation : VNObservation


This type of observation results from performing a VNCoreMLRequest image analysis with a Core ML model whose role is classification (rather than prediction or image-to-image processing). Vision infers that an MLModel object is a classifier model if that model predicts a single feature. That is, the model’s modelDescription object has a non-nil value for its predictedFeatureName property.


Determining Classification

var identifier: String

Classification label identifying the type of observation.

Measuring Confidence and Precision

var hasPrecisionRecallCurve: Bool

A Boolean variable indicating whether the observation contains precision and recall curves.

func hasMinimumPrecision(Float, forRecall: Float) -> Bool

Determines whether the observation for a specific recall has a minimum precision value.

func hasMinimumRecall(Float, forPrecision: Float) -> Bool

Determines whether the observation for a specific precision has a minimum recall value.


Inherits From

Conforms To

See Also

Machine-Learning Image Analysis

Classifying Images with Vision and Core ML

Preprocess photos using the Vision framework and classify them with a Core ML model.

Training a Create ML Model to Classify Flowers

Train a flower classifier using Create ML in Swift Playgrounds, and apply the resulting model to real-time image classification using Vision.

class VNCoreMLRequest

An image analysis request that uses a Core ML model to process images.

class VNPixelBufferObservation

An output image produced by a Core ML image analysis request.

class VNCoreMLFeatureValueObservation

A collection of key-value information produced by a Core ML image analysis request.