Python code for the paper How to scale hyperparameters for quickshift image segmentation

Related tags

Deep Learning quickshift-scale
Overview

How to scale hyperparameters for quickshift image segmentation

Python code for the paper How to scale hyperparameters for quickshift image segmentation

There is nothing to install, one simply has to run the scripts. Some experiments require to download data (additional details are given in the scripts).

Disclaimer

The code was tested with version 0.18.2 of skimage, using another version may lead to unexplained behaviors.

General Organization

The main scripts producing the results and plotting are in the root directory:

  • compute_evolution.py: raw results for the evolution of the number of local maxima and number of superpixels as a function of the image size.
  • plot_evolution.py: plotting the evolution of the number of superpixels as a function of the image size
  • get_segmentations.py: computs segmentations with quickshift and storing the results
  • size_scaling.py: scaling with respect to the size of the images on real data
  • hyperparameter_scaling.py: scaling with respect to the hyperparameters on real data

Auxilliary functions are collected in the utils folder.

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