VapourSynth image segmentation with OpenCV Hierarchical Feature Selection module.
PS: CUDA GPU is a requirement.

Usage

cv_hfs.HFS(vnode clip[, float segEgbThresholdI=0.08, int minRegionSizeI=100, float segEgbThresholdII=0.28, int minRegionSizeII=200, float spatialWeight=0.6, int slicSpixelSize=8, int numSlicIter=5])

Parameters:

• clip
  A clip to process. RGB24 format only.
• segEgbThresholdI
  It is a constant used to threshold weights of the edge when merging adjacent nodes when applying EGB algorithm.
  The segmentation result tends to have more regions remained if this value is large and vice versa.
• minRegionSizeI
  After the EGB segmentation, regions that have fewer pixels then this parameter will be merged into it's adjacent region.
• segEgbThresholdII
  It serves the same purpose as segEgbThresholdI. The segmentation result tends to have more regions remained if this value is large and vice versa.
• minRegionSizeII
  It serves the same purpose as minRegionSizeI.
• spatialWeight
  It describes how important is the role of position when calculating the distance between each pixel and it's center.
  The exact formula to calculate the distance is colorDistance+spatialWeight×spatialDistance.
  The segmentation result tends to have more local consistency if this value is larger.
• slicSpixelSize
  It describes the size of each superpixel when initializing SLIC.
  Every superpixel approximately has slicSpixelSize×slicSpixelSize pixels in the beginning.
• numSlicIter
  It describes how many iteration to perform when executing SLIC.