View Source Evision.StereoMatcher (Evision v0.1.13)
Link to this section Summary
Types
Type that represents an Evision.StereoMatcher
struct.
Functions
Computes disparity map for the specified stereo pair
Computes disparity map for the specified stereo pair
Return
- retval:
int
Python prototype (for reference):
Return
- retval:
int
Python prototype (for reference):
Return
- retval:
int
Python prototype (for reference):
Return
- retval:
int
Python prototype (for reference):
Return
- retval:
int
Python prototype (for reference):
Return
- retval:
int
Python prototype (for reference):
Positional Arguments
- blockSize:
int
Python prototype (for reference):
Positional Arguments
- disp12MaxDiff:
int
Python prototype (for reference):
Positional Arguments
- minDisparity:
int
Python prototype (for reference):
Positional Arguments
- numDisparities:
int
Python prototype (for reference):
Positional Arguments
- speckleRange:
int
Python prototype (for reference):
Positional Arguments
- speckleWindowSize:
int
Python prototype (for reference):
Link to this section Types
@type t() :: %Evision.StereoMatcher{ref: reference()}
Type that represents an Evision.StereoMatcher
struct.
ref.
reference()
The underlying erlang resource variable.
Link to this section Functions
@spec compute(t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}
Computes disparity map for the specified stereo pair
Positional Arguments
left:
Evision.Mat
.Left 8-bit single-channel image.
right:
Evision.Mat
.Right image of the same size and the same type as the left one.
Return
disparity:
Evision.Mat
.Output disparity map. It has the same size as the input images. Some algorithms, like StereoBM or StereoSGBM compute 16-bit fixed-point disparity map (where each disparity value has 4 fractional bits), whereas other algorithms output 32-bit floating-point disparity map.
Python prototype (for reference):
compute(left, right[, disparity]) -> disparity
@spec compute( t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil ) :: Evision.Mat.t() | {:error, String.t()}
Computes disparity map for the specified stereo pair
Positional Arguments
left:
Evision.Mat
.Left 8-bit single-channel image.
right:
Evision.Mat
.Right image of the same size and the same type as the left one.
Return
disparity:
Evision.Mat
.Output disparity map. It has the same size as the input images. Some algorithms, like StereoBM or StereoSGBM compute 16-bit fixed-point disparity map (where each disparity value has 4 fractional bits), whereas other algorithms output 32-bit floating-point disparity map.
Python prototype (for reference):
compute(left, right[, disparity]) -> disparity
Return
- retval:
int
Python prototype (for reference):
getBlockSize() -> retval
Return
- retval:
int
Python prototype (for reference):
getDisp12MaxDiff() -> retval
Return
- retval:
int
Python prototype (for reference):
getMinDisparity() -> retval
Return
- retval:
int
Python prototype (for reference):
getNumDisparities() -> retval
Return
- retval:
int
Python prototype (for reference):
getSpeckleRange() -> retval
Return
- retval:
int
Python prototype (for reference):
getSpeckleWindowSize() -> retval
Positional Arguments
- blockSize:
int
Python prototype (for reference):
setBlockSize(blockSize) -> None
Positional Arguments
- disp12MaxDiff:
int
Python prototype (for reference):
setDisp12MaxDiff(disp12MaxDiff) -> None
Positional Arguments
- minDisparity:
int
Python prototype (for reference):
setMinDisparity(minDisparity) -> None
Positional Arguments
- numDisparities:
int
Python prototype (for reference):
setNumDisparities(numDisparities) -> None
Positional Arguments
- speckleRange:
int
Python prototype (for reference):
setSpeckleRange(speckleRange) -> None
Positional Arguments
- speckleWindowSize:
int
Python prototype (for reference):
setSpeckleWindowSize(speckleWindowSize) -> None