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Corrosion Images Classification to Improve Industrial Corrosion Management

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CorrSave User Manual

Corrosion Images Classification to Improve Industrial Corrosion Management

This application use machine learning (convolutional neural network & image processing features) to classify the material corrosiveness. Application link:

Option 1: Use our pre-trained model to test your data.

  1. Download pre-trained model from https://github.com/nurafiqah78/CorrSave/blob/master/pre-trained_model%202019-05-16%2010.37.57
  2. skip Tab 1 as you already has the scale attributes ready from the trained model.
  3. Download scale attributes file from https://github.com/nurafiqah78/CorrSave/blob/master/Scale%20Attribute.csv
  4. Tab 2 (Pre-Train Model): upload (1.) Model File and (2.) ScaleAttribute File
  5. Tab 3 (Test Model): Upload your test data (1 image, URL or multiple images in older)

Option 2: Train your own datasets.

  1. Separate your datasets into 2 folders (0: corroded , 1: non corroded)
  2. Tab 1 (Model Initialization): set your own parameters
  3. Tab 2 (Train Model): upload class 0 and class 1 folders
  4. click 'Calculate features' and 'start training'
  5. Tab 3 (Test Model): Upload your test data (1 image, URL or multiple images in older)

You may refer to Documentation (https://github.com/nurafiqah78/CorrSave/blob/master/Corrosion_Classification_Documentation.pdf) and shinyapp slide (http:https://rpubs.com/oryzalee/500830) for more info.

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