# View Source Evision.HausdorffDistanceExtractor (Evision v0.1.28)

# Link to this section Summary

## Functions

getDistanceFlag

getRankProportion

Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm.

This method sets the rank proportion (or fractional value) that establish the Kth ranked value of the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare shapes.

# Link to this section Types

@type t() :: %Evision.HausdorffDistanceExtractor{ref: reference()}

Type that represents an `HausdorffDistanceExtractor`

struct.

**ref**.`reference()`

The underlying erlang resource variable.

# Link to this section Functions

getDistanceFlag

##### Positional Arguments

**self**:`Evision.HausdorffDistanceExtractor.t()`

##### Return

**retval**:`int`

Python prototype (for reference only):

`getDistanceFlag() -> retval`

getRankProportion

##### Positional Arguments

**self**:`Evision.HausdorffDistanceExtractor.t()`

##### Return

**retval**:`float`

Python prototype (for reference only):

`getRankProportion() -> retval`

Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm.

##### Positional Arguments

**self**:`Evision.HausdorffDistanceExtractor.t()`

**distanceFlag**:`int`

.Flag indicating which norm is used to compute the Hausdorff distance (NORM_L1, NORM_L2).

Python prototype (for reference only):

`setDistanceFlag(distanceFlag) -> None`

This method sets the rank proportion (or fractional value) that establish the Kth ranked value of the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare shapes.

##### Positional Arguments

**self**:`Evision.HausdorffDistanceExtractor.t()`

**rankProportion**:`float`

.fractional value (between 0 and 1).

Python prototype (for reference only):

`setRankProportion(rankProportion) -> None`