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Model MobileNet

Model MobileNet Node Documentation
The Model MobileNet node in AugeLab Studio represents the MobileNet model for deep learning tasks.
Node Overview
The Model MobileNet node allows you to create a MobileNet model for image classification. It has the following properties:
Node Title: Model MobileNet
Node ID: OP_NODE_AI_MOBILENET_V2
Inputs
The Model MobileNet node requires the following input:
Input Image: Connect an image data source to the node.
Outputs
The Model MobileNet node outputs the created MobileNet model.
Node Interaction
1.Drag and drop the Model MobileNet node from the node library onto the canvas in AugeLab Studio.
2.Connect an image data source to the node.
3.Configure the node properties:
Model Type: Choose the MobileNet model type from the dropdown list.
Input Size: Specify the input size of the images.
Model Width: Adjust the width of the MobileNet model using the slider.
Pooling: Choose the pooling mode (Maximum, Average, or None).
4.The MobileNet model will be created and outputted by the node.
Implementation Details
The Model MobileNet node is implemented as a subclass of the NodeCNN base class. It overrides the evalAi method to create the MobileNet model.
The Model MobileNet node requires an image data source as input.
The node validates the input size and ensures it is greater than or equal to 32.
The node checks if the input images are in RGB format and raises an error if they are not.
The MobileNet model is created using the specified model type, input size, model width, and pooling mode.
The created model is added to the PNNModel object.
The PNNModel object, containing the MobileNet model, is returned as the output.
Usage
1.Drag and drop the Model MobileNet node from the node library onto the canvas in AugeLab Studio.
2.Connect an image data source to the node.
3.Configure the node properties:
Model Type: Choose the MobileNet model type (MobileNet, MobileNetV2, MobileNetV3 Small, or MobileNetV3 Large).
Input Size: Specify the input size of the images.
Model Width: Adjust the width of the MobileNet model using the slider.
Pooling: Choose the pooling mode (Maximum, Average, or None).
4.The MobileNet model will be created based on the specified configuration.
5.Use the output MobileNet model for image classification tasks or connect it to other nodes for further processing.
Notes
The Model MobileNet node allows you to create MobileNet models for image classification.
It expects the Keras library to be installed.
The node requires an image data source as input.
The input images should be in RGB format. Grayscale images are not supported.
The MobileNet models have different versions and complexity levels. Choose the appropriate model type based on your requirements.
The input size specifies the height and width dimensions of the input images. It should be greater than or equal to 32.
The model width parameter adjusts the width of the MobileNet model. It ranges from 0 to 100 percent, allowing you to control the model's computational complexity.
The pooling mode determines how the spatial dimensions of the output are reduced. Choose between Maximum, Average, or No pooling.
The output MobileNet model can be used for image classification tasks.
Connect the output of the Model MobileNet node to other nodes for further processing, such as training, evaluation, or prediction.
Experiment with different MobileNet model types, input sizes, model widths, and pooling modes to achieve optimal results for your image classification tasks.
The Model MobileNet node is particularly useful for computer vision tasks, such as object recognition or image classification.

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