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StereoSGBM

stereoclassOpenCV 5.0.0
import { StereoSGBM } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Native object: release it with using or delete(). Factories can return null; check before calling methods. Inherits StereoMatcher.

The class implements the modified H. Hirschmuller algorithm [HH08] that differs from the original one as follows:

  • By default, the algorithm is single-pass, which means that you consider only 5 directions instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the algorithm but beware that it may consume a lot of memory.
  • The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the blocks to single pixels.
  • Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi sub-pixel metric from [BT98] is used. Though, the color images are supported as well.
  • Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness check, quadratic interpolation and speckle filtering).

Note: - (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found at opencv_source_code/samples/python/stereo_match.py

Constructors and members

static create

Creates StereoSGBM object

create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number, uniquenessRatio: number, speckleWindowSize: number, speckleRange: number, mode: number): StereoSGBM | null;
12 available overloads
create(): StereoSGBM | null;
create(minDisparity: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number, uniquenessRatio: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number, uniquenessRatio: number, speckleWindowSize: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number, uniquenessRatio: number, speckleWindowSize: number, speckleRange: number): StereoSGBM | null;
create(minDisparity: number, numDisparities: number, blockSize: number, P1: number, P2: number, disp12MaxDiff: number, preFilterCap: number, uniquenessRatio: number, speckleWindowSize: number, speckleRange: number, mode: number): StereoSGBM | null;
minDisparity

Minimum possible disparity value. Normally, it is zero but sometimes rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.

numDisparities

Maximum disparity minus minimum disparity. The value is always greater than zero. In the current implementation, this parameter must be divisible by 16.

blockSize

Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range.

P1

The first parameter controlling the disparity smoothness. See below.

P2

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

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

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

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

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

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

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 .

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.

Returns

The StereoSGBM | null result.

clone

Create another handle to the same native object. This retains the object without copying its pixels or algorithm state; dispose both handles separately.

clone(): this;
Returns

The this result.

getPreFilterCap

Return the pre filter cap configured on this StereoSGBM object.

getPreFilterCap(): number;
Returns

The number result.

setPreFilterCap

Set the pre filter cap used by this StereoSGBM object.

setPreFilterCap(preFilterCap: number): void;
preFilterCap

pre filter cap argument (number).

getUniquenessRatio

Return the uniqueness ratio configured on this StereoSGBM object.

getUniquenessRatio(): number;
Returns

The number result.

setUniquenessRatio

Set the uniqueness ratio used by this StereoSGBM object.

setUniquenessRatio(uniquenessRatio: number): void;
uniquenessRatio

uniqueness ratio argument (number).

getP1

Return the p1 configured on this StereoSGBM object.

getP1(): number;
Returns

The number result.

setP1

Set the p1 used by this StereoSGBM object.

setP1(P1: number): void;
P1

p1 argument (number).

getP2

Return the p2 configured on this StereoSGBM object.

getP2(): number;
Returns

The number result.

setP2

Set the p2 used by this StereoSGBM object.

setP2(P2: number): void;
P2

p2 argument (number).

getMode

Return the mode configured on this StereoSGBM object.

getMode(): number;
Returns

The number result.

setMode

Set the mode used by this StereoSGBM object.

setMode(mode: number): void;
mode

mode argument (number).

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.