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Use it for various segmentation tasks. Features include image label creation, ResNet34 neural network model (arch) training and image prediction.

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Segmentation App

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About

Based on the bachelor-thesis "Microstructure analysis of materials with the assistance of artificial technology" by Kerim Yalcin from Feb 2024.

Features:

  • read and save image files
  • use filters to change brightness and gaussian-blur amount of loaded images
  • apply binarization and tresholding
  • trace boundaries using resizable brush tool in black or white
  • create image labels for a Resnet34 model (max. 2 classifications)
  • create and train a ResNet34 model with created labels
  • predict images using a trained ResNet34 model

manualSegmentation.py

Use this script for manual label creation. Image of manualSegmentation.py after loading an image and tracing.

semanticSegmentation.py

Use this script for creating and training a ResNet34 model. Predict images using the trained model. Image of semanticSegmentation.py after predicting an image using a trained model

Installation

The application can either be started by using the executable or directly by running the scripts after installing Python and the required packages.

Installing the Executable

Installing Python

Installing required packages

Manual

Notice

  • Reading and saving image file names are not supported in Unicode due to OpenCV imread and imwrite function
  • Cancelling the file dialog without selecting a path can lead to termination of the app
  • an internet connection is required to create the ResNet32 model

About

Use it for various segmentation tasks. Features include image label creation, ResNet34 neural network model (arch) training and image prediction.

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