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KNIME_​project.knar

Now we feed the training set to the Artificial Neural Network so that it can train to evaluate thenudity coefficient of people in photos. The ANN is developed through the use of a ConvolutionalNeural Network embedded in the Python node.Of course we use Convolution2D as we aredealing with images in two dimension Node 36Node 39labels Anaconda preparedEnvironmentInput 150x150x3Node 911Filters: 32Kernel size:5x5Stride:1x1Activation:ReLUPool size:2x2Stride:1x1Filters:64Kernel size:5x5Stride:1x1Activation:ReLUPool size:2x2Stride:1x1Pool size:2x2Stride:1x1Filters:128Kernel size:5x5Stride:1x1Activation:ReLUPool size:3x3Stride:1x1Filters:256Kernel size:5x5Stride:1x1Activation:ReLUUnits:256Activation:ReLUUnits:100Activation:ReLUUnits:64Activation:ReLUUnits:32Activation:ReLUUnits:10Activation:ReLUUnits:1Activation:SigmoidNode 930Node 936Node 937from unsignedbyte to floatNode 942Node 944Node 945Node 946Python Script Python Script File Reader(deprecated) Column Appender Conda EnvironmentPropagation Keras Input Layer DL PythonNetwork Creator Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Flatten Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor List Files/Folders Image Calculator Create CollectionColumn Path to String List Files/Folders Image Reader(Table) Image Resizer Now we feed the training set to the Artificial Neural Network so that it can train to evaluate thenudity coefficient of people in photos. The ANN is developed through the use of a ConvolutionalNeural Network embedded in the Python node.Of course we use Convolution2D as we aredealing with images in two dimension Node 36Node 39labels Anaconda preparedEnvironmentInput 150x150x3Node 911Filters: 32Kernel size:5x5Stride:1x1Activation:ReLUPool size:2x2Stride:1x1Filters:64Kernel size:5x5Stride:1x1Activation:ReLUPool size:2x2Stride:1x1Pool size:2x2Stride:1x1Filters:128Kernel size:5x5Stride:1x1Activation:ReLUPool size:3x3Stride:1x1Filters:256Kernel size:5x5Stride:1x1Activation:ReLUUnits:256Activation:ReLUUnits:100Activation:ReLUUnits:64Activation:ReLUUnits:32Activation:ReLUUnits:10Activation:ReLUUnits:1Activation:SigmoidNode 930Node 936Node 937from unsignedbyte to floatNode 942Node 944Node 945Node 946Python Script Python Script File Reader(deprecated) Column Appender Conda EnvironmentPropagation Keras Input Layer DL PythonNetwork Creator Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Flatten Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor List Files/Folders Image Calculator Create CollectionColumn Path to String List Files/Folders Image Reader(Table) Image Resizer

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Costi
Created at: 2021-12-05
On NodePit since: 2022-02-06
Last update: 2024-05-03
Created with KNIME version: v4.4.2

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