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Multiclass-Semantic-Segmentation-Annotation with tool-usage-codes

Main image to be annotated is: Main image

The annotated image (grayscale 1 channel) for separate classes: Annotated image

Installation

conda install -c anaconda pillow
conda install -c anaconda opencv
conda install -c anaconda matplotlib
conda install anaconda::scikit-image
conda install anaconda::pandas

Step by step guideline

  • First, download the Fiji software for annotating for semantic segmentation.
  • Secondly, unzip and open the tool from ImageJ-win64.exe.
  • Then follow: File (tab) > Open > desired_image > Plugins (tab) > Labkit > Open Current Image with Labkit
  • Later, use Draw, Flood fill, Erase to draw masks for desired classes. To add more classes, click 'Add Label' button. Complete drawing mask accordingly for each classes. Don't forget to add background (can use Flood fill) at the end as a class.
  • For each class, click the 'Export as Bitmap..' button to save the binary semantic segmentation mask image (in .tif format) for each class.
  • Save all the binary mask for each class like previous step.
  • Lastly, run the python code (Multiclass semantic segmentation annotation.ipynb) to make a multiclass semantic segmentation mask in grayscale. Make sure to change the name of binary mask files and the desired label of each class in the python code.