|
|
|
|
AIDetectModel (Function) In french: IAModèleDétecte Runs a trained neural network model on an image. This function allows you to use artificial intelligence to detect objects in an image. Caution: This function is an advanced function. To use this function, it is recommended to read the documentation of the neural network used (specifics, expected results and interpretation). // Image declaration MyImage is Image MyImage = IMG_Test  // Declare a model MyAINNModel is aiNeuralNetworkModel  MyAINNModel.Configuration = "MyModel.cfg" MyAINNModel.TrainedWeights = "MyModel.weights.pb" MyAINNModel.PixelScaleFactor = 1.0  // Caution: the X and Y dimensions depend on the model. // If the specified dimensions do not match the model, // AIDetectModel returns an error. MyAINNModel.XDimension = 300 MyAINNModel.YDimension = 300  MyAINNModel.AverageIntensityR = 104 MyAINNModel.AverageIntensityG = 117 MyAINNModel.AverageIntensityB = 113 MyAINNModel.RGBColor = True  myMatrixArray is array of 1 array of 1 by 1 by 200 by 7 real  // Run model myMatrixArray = AIDetectModel(MyAINNModel, MyImage) Syntax
<Result> = AIDetectModel(<Model> , <Image>)
<Result>: Array of array Array of matrices containing the result of the execution of the model. This array is specific to each model and must be known by the developer. <Model>: aiNeuralNetworkModel variable Name of the aiNeuralNetworkModel variable describing the characteristics of the neural network used. Caution: The different characteristics of this variable are specific to each model and must be known by the developer. <Image>: String, Image or Image control Image to be analyzed. The image can correspond to: - a variable of type Image,
- the name and path of the image,
- the name and path of a PDF file,
- an Image memo item,
- an Image control.
Remarks - The AI engine used by AIDetectModel is OpenCV. This engine reads the AI models and executes them.
- The supported neural network models are:
- caffe,
- tensorflow,
- darknet,
New in version 2024onnx
- The model must be trained (weights are known).
- The expected extensions according to the models are:
- Configuration:
- Caffe: *.prototxt
- Tensorflow: *.pbtxt
- Darknet: *.cfg
- Weights:
- Caffe: *.caffemodel
- Tensorflow: *.pb
- Darknet: *.weights
New in version 2024Open Neural Network Exchange (ONNX): *.onnx
Business / UI classification: Business Logic
This page is also available for…
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|