View Source Evision.StereoSGBM (Evision v0.1.13)
Link to this section Summary
Types
Type that represents an Evision.StereoSGBM
struct.
Functions
Computes disparity map for the specified stereo pair
Computes disparity map for the specified stereo pair
Creates StereoSGBM object
Creates StereoSGBM object
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):
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
- mode:
int
Python prototype (for reference):
Positional Arguments
- numDisparities:
int
Python prototype (for reference):
Positional Arguments
- p1:
int
Python prototype (for reference):
Positional Arguments
- p2:
int
Python prototype (for reference):
Positional Arguments
- preFilterCap:
int
Python prototype (for reference):
Positional Arguments
- speckleRange:
int
Python prototype (for reference):
Positional Arguments
- speckleWindowSize:
int
Python prototype (for reference):
Positional Arguments
- uniquenessRatio:
int
Python prototype (for reference):
Link to this section Types
@type t() :: %Evision.StereoSGBM{ref: reference()}
Type that represents an Evision.StereoSGBM
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
Creates StereoSGBM object
Keyword Arguments
minDisparity:
int
.Minimum possible disparity value. Normally, it is zero but sometimes rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
numDisparities:
int
.Maximum disparity minus minimum disparity. The value is always greater than zero. In the current implementation, this parameter must be divisible by 16.
blockSize:
int
.Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range.
p1:
int
.The first parameter controlling the disparity smoothness. See below.
p2:
int
.The second parameter controlling the disparity smoothness. The larger the values are, the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor pixels. The algorithm requires P2 > P1 . See stereo_match.cpp sample where some reasonably good P1 and P2 values are shown (like 8*number_of_image_channels*blockSize*blockSize and 32*number_of_image_channels*blockSize*blockSize , respectively).
disp12MaxDiff:
int
.Maximum allowed difference (in integer pixel units) in the left-right disparity check. Set it to a non-positive value to disable the check.
preFilterCap:
int
.Truncation value for the prefiltered image pixels. The algorithm first computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. The result values are passed to the Birchfield-Tomasi pixel cost function.
uniquenessRatio:
int
.Margin in percentage by which the best (minimum) computed cost function value should "win" the second best value to consider the found match correct. Normally, a value within the 5-15 range is good enough.
speckleWindowSize:
int
.Maximum size of smooth disparity regions to consider their noise speckles and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the 50-200 range.
speckleRange:
int
.Maximum disparity variation within each connected component. If you do speckle filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. Normally, 1 or 2 is good enough.
mode:
int
.Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming algorithm. It will consume O(W*H*numDisparities) bytes, which is large for 640x480 stereo and huge for HD-size pictures. By default, it is set to false .
Return
- retval:
Evision.StereoSGBM
The first constructor initializes StereoSGBM with all the default parameters. So, you only have to set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter to a custom value.
Python prototype (for reference):
create([, minDisparity[, numDisparities[, blockSize[, P1[, P2[, disp12MaxDiff[, preFilterCap[, uniquenessRatio[, speckleWindowSize[, speckleRange[, mode]]]]]]]]]]]) -> retval
Creates StereoSGBM object
Keyword Arguments
minDisparity:
int
.Minimum possible disparity value. Normally, it is zero but sometimes rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
numDisparities:
int
.Maximum disparity minus minimum disparity. The value is always greater than zero. In the current implementation, this parameter must be divisible by 16.
blockSize:
int
.Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range.
p1:
int
.The first parameter controlling the disparity smoothness. See below.
p2:
int
.The second parameter controlling the disparity smoothness. The larger the values are, the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor pixels. The algorithm requires P2 > P1 . See stereo_match.cpp sample where some reasonably good P1 and P2 values are shown (like 8*number_of_image_channels*blockSize*blockSize and 32*number_of_image_channels*blockSize*blockSize , respectively).
disp12MaxDiff:
int
.Maximum allowed difference (in integer pixel units) in the left-right disparity check. Set it to a non-positive value to disable the check.
preFilterCap:
int
.Truncation value for the prefiltered image pixels. The algorithm first computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. The result values are passed to the Birchfield-Tomasi pixel cost function.
uniquenessRatio:
int
.Margin in percentage by which the best (minimum) computed cost function value should "win" the second best value to consider the found match correct. Normally, a value within the 5-15 range is good enough.
speckleWindowSize:
int
.Maximum size of smooth disparity regions to consider their noise speckles and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the 50-200 range.
speckleRange:
int
.Maximum disparity variation within each connected component. If you do speckle filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. Normally, 1 or 2 is good enough.
mode:
int
.Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming algorithm. It will consume O(W*H*numDisparities) bytes, which is large for 640x480 stereo and huge for HD-size pictures. By default, it is set to false .
Return
- retval:
Evision.StereoSGBM
The first constructor initializes StereoSGBM with all the default parameters. So, you only have to set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter to a custom value.
Python prototype (for reference):
create([, minDisparity[, numDisparities[, blockSize[, P1[, P2[, disp12MaxDiff[, preFilterCap[, uniquenessRatio[, speckleWindowSize[, speckleRange[, mode]]]]]]]]]]]) -> retval
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):
getMode() -> retval
Return
- retval:
int
Python prototype (for reference):
getNumDisparities() -> retval
Return
- retval:
int
Python prototype (for reference):
getP1() -> retval
Return
- retval:
int
Python prototype (for reference):
getP2() -> retval
Return
- retval:
int
Python prototype (for reference):
getPreFilterCap() -> retval
Return
- retval:
int
Python prototype (for reference):
getSpeckleRange() -> retval
Return
- retval:
int
Python prototype (for reference):
getSpeckleWindowSize() -> retval
Return
- retval:
int
Python prototype (for reference):
getUniquenessRatio() -> 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
- mode:
int
Python prototype (for reference):
setMode(mode) -> None
Positional Arguments
- numDisparities:
int
Python prototype (for reference):
setNumDisparities(numDisparities) -> None
Positional Arguments
- p1:
int
Python prototype (for reference):
setP1(P1) -> None
Positional Arguments
- p2:
int
Python prototype (for reference):
setP2(P2) -> None
Positional Arguments
- preFilterCap:
int
Python prototype (for reference):
setPreFilterCap(preFilterCap) -> None
Positional Arguments
- speckleRange:
int
Python prototype (for reference):
setSpeckleRange(speckleRange) -> None
Positional Arguments
- speckleWindowSize:
int
Python prototype (for reference):
setSpeckleWindowSize(speckleWindowSize) -> None
Positional Arguments
- uniquenessRatio:
int
Python prototype (for reference):
setUniquenessRatio(uniquenessRatio) -> None