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Input Layer 2D
The
Input Layer 2D node in AugeLab Studio is used to define the input layer for a 2D convolutional neural network (CNN). It represents the initial layer of the network that takes input images.The
Input Layer 2D node defines the input layer for a 2D CNN. It has the following properties:- Node Title: Input Layer 2D
- Node ID: OP_NODE_AI_2D_INPUT_CONV_LAYER
The
Input Layer 2D node has the following input socket:- Folder: A folder containing the input images for training the CNN.
The
Input Layer 2D node outputs the configured PNNModel object, which represents the CNN model architecture with the input layer defined.- 1.Drag and drop the
Input Layer 2Dnode from the node library onto the canvas in AugeLab Studio. - 2.Connect the
Folderinput socket of theInput Layer 2Dnode to aChoose Folder 2Dblock that specifies the folder containing the input images. - 3.Configure the properties of the
Input Layer 2Dnode, such as the input size. - 4.Connect the output of the
Input Layer 2Dnode to other nodes in the network to build the CNN architecture.
The
Input Layer 2D node is implemented using the Input layer from the Keras library. The node's evalAi method constructs the input layer based on the specified input size and color type.- The
Input Layer 2Dnode expects an input folder containing the training images. - It determines the color type of the input images and constructs the input layer accordingly.
- The input size defines the height and width of the input images.
- The
Input Layer 2Dnode configures thePNNModelobject with the input layer and input size.
- 1.Drag and drop the
Input Layer 2Dnode from the node library onto the canvas in AugeLab Studio. - 2.Connect the
Folderinput socket of theInput Layer 2Dnode to aChoose Folder 2Dblock that specifies the folder containing the input images. - 3.Configure the properties of the
Input Layer 2Dnode, such as the input size. - 4.Connect the output of the
Input Layer 2Dnode to other nodes in the network to build the CNN architecture. - 5.Train the network using the configured input layer and observe the results.
- The
Input Layer 2Dnode defines the input layer for a 2D CNN. - It takes a folder containing the input images as input.
- The
Input Layer 2Dnode requires the Keras library to be installed. - Ensure that the input folder contains the training images in the appropriate format.
- The
Input Layer 2Dnode outputs the configuredPNNModelobject, which represents the CNN model architecture with the input layer defined. - Connect the output of the
Input Layer 2Dnode to other nodes in the network to build the CNN architecture. - The input size defines the height and width of the input images for training the CNN.