ClassificationModel class

Constructors

ClassificationModel.new(int _index, List<String> labels, int imageWidth, int imageHeight)

Properties

hashCode → int

The hash code for this object.

no setter, inherited

imageHeight → int

final

imageWidth → int

final

labels → List<String>

final

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

getCameraImagePrediction(CameraImage cameraImage, {int? rotation, List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, CameraPreProcessingMethod cameraPreProcessingMethod = CameraPreProcessingMethod.imageLib, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<String>

Retrieves the top prediction label for a camera image.

getCameraImagePredictionList(CameraImage cameraImage, {int? rotation, List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, CameraPreProcessingMethod cameraPreProcessingMethod = CameraPreProcessingMethod.imageLib, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<List<double>>

Retrieves a list of predictions for a camera image.

getCameraImagePredictionProbabilities(CameraImage cameraImage, {int? rotation, List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, CameraPreProcessingMethod cameraPreProcessingMethod = CameraPreProcessingMethod.imageLib, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<List<double>>

Retrieves the probabilities of predictions for a camera image.

getImagePrediction(Uint8List imageAsBytes, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<String>

Returns the predicted image label using the given imageAsBytes.

getImagePredictionFromBytesList(List<Uint8List> imageAsBytesList, int imageWidth, int imageHeight, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB}) → Future<String>

Returns the predicted label for an image as a bytes list.. The image are passed as a list of Uint8List objects. The imageWidth and imageHeight parameters specify the dimensions of the image. The optional mean and std parameters can be used to normalize the image. Returns a Future that resolves to a String representing the predicted label.

getImagePredictionList(Uint8List imageAsBytes, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<List<double>>

Returns the predicted image as a list of scores using the given imageAsBytes.

getImagePredictionListFromBytesList(List<Uint8List> imageAsBytesList, int imageWidth, int imageHeight, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB}) → Future<List<double>>

Returns a list of predictions for an image as a bytes list. The image are passed as a list of Uint8List objects. The imageWidth and imageHeight parameters specify the dimensions of the image. The optional mean and std parameters can be used to normalize the image. Returns a Future that resolves to a list of double values representing the predictions.

getImagePredictionListProbabilities(Uint8List imageAsBytes, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB, PreProcessingMethod preProcessingMethod = PreProcessingMethod.imageLib}) → Future<List<double>>

Returns the predicted image probabilities using the given imageAsBytes.

getImagePredictionListProbabilitiesFromBytesList(List<Uint8List> imageAsBytesList, int imageWidth, int imageHeight, {List<double> mean = torchVisionNormMeanRGB, List<double> std = torchVisionNormSTDRGB}) → Future<List<double>>

Returns a list of probabilities for an image as a bytes list. The image are passed as a list of Uint8List objects. The imageWidth and imageHeight parameters specify the dimensions of the image. The optional mean and std parameters can be used to normalize the image. Returns a Future that resolves to a list of double values representing the probabilities.

getProbabilities(List<double> prediction) → List<double>

Returns the probabilities of each element in the prediction list using the softmax function.

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

softMax(List<double?> prediction) → int

Returns the index of the maximum value in the prediction list using the softmax function.

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited