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- Properties specific to aiNeuralNetworkModel variables
aiNeuralNetworkModel (Variable type)
The aiNeuralNetworkModel type is used to define all the advanced characteristics of a neural network used by AIDetectModel. You can define and change the characteristics of this neural network using different WLanguage properties. Note: For more details on the declaration of this type of variable and the use of WLanguage properties, see Declaring a variable.
MonImage is Image
MonImage = IMG_Test
MonIAModèleRN is aiNeuralNetworkModel
MonIAModèleRN.Configuration = "MonModel.cfg"
MonIAModèleRN.TrainedWeights = "MonModel.weights.pb"
MonIAModèleRN.PixelScaleFactor = 1.0
MonIAModèleRN.XDimension = 300
MonIAModèleRN.YDimension = 300
MonIAModèleRN.AverageIntensityR = 104
MonIAModèleRN.AverageIntensityG = 117
MonIAModèleRN.AverageIntensityB = 113
MonIAModèleRN.RGBColor = True
montabMatrice is array of 1 array of 1 by 1 by 200 by 7 reals
montabMatrice = AIDetectModel(MonIAModèleRN, MonImage)
Propiedades Properties specific to aiNeuralNetworkModel variables The following properties can be used to handle a neural network model: | | | | Property name | Type used | Effect |
|---|
| AverageIntensityB | Integer | Average intensity of the Blue (B) color in the training data. This property is optional. | | AverageIntensityG | Integer | Average intensity of the Green (G) color in the training data. This property is optional. | | AverageIntensityR | Integer | Average intensity of the Red (R) color in the training data. This property is optional. | | Configuration | Character string | Full path of the file that contains the configuration of the model. Note: The following configuration types are possible: - Caffe: *.prototxt
- Tensorflow: *.pbtxt
- Darknet: *.cfg
| | OutputLayerName | Character string | Name of the output neural network layer. | | PixelScaleFactor | Real | Used to scale pixel values. Set to 1.0 by default (no scaling). | | RGBColor | Boolean | - True if the provided images are encoded in RGB. In this case, the conversion to BGR encoding will be done automatically.
- False (default value) if the provided images are encoded in BGR.
This property is optional. | | TrainedWeights | Character string | Full path of the file that contains the trained weights of the model. Note: The following weight types are available: - Caffe: *.caffemodel
- Tensorflow: *.pb
- Darknet: *.weights
- Open Neural Network Exchange (ONNX): *.onnx
| | TransposeRequired | Boolean | - if transposition is required,
- False otherwise.
When to use this property?
OpenCV creates matrices based on images and defines them as "Number of columns, Number of rows, Number of channels".
Some models expect matrices with the following format: "Number of channels, Number of columns, Number of rows". This means it is necessary to modify the matrix representation of the image created by OpenCV. | | XDimension | Integer | Image size required by the model: value corresponding to X. By default, this property corresponds to the width of the image. | | YDimension | Integer | Image size required by the model: value corresponding to Y. By default, this property corresponds to the height of the image. |
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