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Data Science Bowl 2018

YOLOv3 model YOLOv3 model

🏃 Kaggle competition

This repository contains data analysis for Data Science Bowl 2018 kaggle competition. Main purpose is nucleuses identification (segmentation) in varied conditions.

📈 Data analysis

Firstly, exploratory data analysis was conducted to get to know with data. Results can be found here.

It contains observations for:

  • Files (filename encoding, directory structure, duplicated files and data format)
  • Train and test data (distribution)
  • Dimensions (width and height)
  • Channels visualisation
  • Colour models (division into colour and black&white images based on channels)
  • Masks (number of masks and how many pixels are considered as a nucleus)
  • Outliers

I have also proved that train and test data is from the same distribution using adversarial validation.

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Nucleuses segmentation in varied conditions

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