//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.calib3d;
import org.opencv.calib3d.StereoMatcher;
import org.opencv.calib3d.StereoSGBM;
// C++: class StereoSGBM
/**
* The class implements the modified H. Hirschmuller algorithm CITE: HH08 that differs from the original
* one as follows:
*
* <ul>
* <li>
* 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.
* </li>
* <li>
* The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the
* blocks to single pixels.
* </li>
* <li>
* Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi
* sub-pixel metric from CITE: BT98 is used. Though, the color images are supported as well.
* </li>
* <li>
* 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).
* </li>
* </ul>
*
* <b>Note:</b>
* <ul>
* <li>
* (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found
* at opencv_source_code/samples/python/stereo_match.py
* </li>
* </ul>
*/
public class StereoSGBM extends StereoMatcher {
protected StereoSGBM(long addr) { super(addr); }
// internal usage only
public static StereoSGBM __fromPtr__(long addr) { return new StereoSGBM(addr); }
// C++: enum <unnamed>
public static final int
MODE_SGBM = 0,
MODE_HH = 1,
MODE_SGBM_3WAY = 2,
MODE_HH4 = 3;
//
// C++: int cv::StereoSGBM::getPreFilterCap()
//
public int getPreFilterCap() {
return getPreFilterCap_0(nativeObj);
}
//
// C++: void cv::StereoSGBM::setPreFilterCap(int preFilterCap)
//
public void setPreFilterCap(int preFilterCap) {
setPreFilterCap_0(nativeObj, preFilterCap);
}
//
// C++: int cv::StereoSGBM::getUniquenessRatio()
//
public int getUniquenessRatio() {
return getUniquenessRatio_0(nativeObj);
}
//
// C++: void cv::StereoSGBM::setUniquenessRatio(int uniquenessRatio)
//
public void setUniquenessRatio(int uniquenessRatio) {
setUniquenessRatio_0(nativeObj, uniquenessRatio);
}
//
// C++: int cv::StereoSGBM::getP1()
//
public int getP1() {
return getP1_0(nativeObj);
}
//
// C++: void cv::StereoSGBM::setP1(int P1)
//
public void setP1(int P1) {
setP1_0(nativeObj, P1);
}
//
// C++: int cv::StereoSGBM::getP2()
//
public int getP2() {
return getP2_0(nativeObj);
}
//
// C++: void cv::StereoSGBM::setP2(int P2)
//
public void setP2(int P2) {
setP2_0(nativeObj, P2);
}
//
// C++: int cv::StereoSGBM::getMode()
//
public int getMode() {
return getMode_0(nativeObj);
}
//
// C++: void cv::StereoSGBM::setMode(int mode)
//
public void setMode(int mode) {
setMode_0(nativeObj, mode);
}
//
// C++: static Ptr_StereoSGBM cv::StereoSGBM::create(int minDisparity = 0, int numDisparities = 16, int blockSize = 3, int P1 = 0, int P2 = 0, int disp12MaxDiff = 0, int preFilterCap = 0, int uniquenessRatio = 0, int speckleWindowSize = 0, int speckleRange = 0, int mode = StereoSGBM::MODE_SGBM)
//
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize, int speckleRange, int mode) {
return StereoSGBM.__fromPtr__(create_0(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff, preFilterCap, uniquenessRatio, speckleWindowSize, speckleRange, mode));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize, int speckleRange) {
return StereoSGBM.__fromPtr__(create_1(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff, preFilterCap, uniquenessRatio, speckleWindowSize, speckleRange));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* @param 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.
* @param 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.
* @param 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.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize) {
return StereoSGBM.__fromPtr__(create_2(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff, preFilterCap, uniquenessRatio, speckleWindowSize));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* @param 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.
* @param 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.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio) {
return StereoSGBM.__fromPtr__(create_3(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff, preFilterCap, uniquenessRatio));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* @param 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap) {
return StereoSGBM.__fromPtr__(create_4(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff, preFilterCap));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* @param 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.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff) {
return StereoSGBM.__fromPtr__(create_5(minDisparity, numDisparities, blockSize, P1, P2, disp12MaxDiff));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* @param 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1, int P2) {
return StereoSGBM.__fromPtr__(create_6(minDisparity, numDisparities, blockSize, P1, P2));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* @param P1 The first parameter controlling the disparity smoothness. See below.
* 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize, int P1) {
return StereoSGBM.__fromPtr__(create_7(minDisparity, numDisparities, blockSize, P1));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* @param blockSize Matched block size. It must be an odd number >=1 . Normally, it should be
* somewhere in the 3..11 range.
* 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities, int blockSize) {
return StereoSGBM.__fromPtr__(create_8(minDisparity, numDisparities, blockSize));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
* zero. In the current implementation, this parameter must be divisible by 16.
* somewhere in the 3..11 range.
* 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity, int numDisparities) {
return StereoSGBM.__fromPtr__(create_9(minDisparity, numDisparities));
}
/**
* Creates StereoSGBM object
*
* @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* zero. In the current implementation, this parameter must be divisible by 16.
* somewhere in the 3..11 range.
* 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create(int minDisparity) {
return StereoSGBM.__fromPtr__(create_10(minDisparity));
}
/**
* Creates StereoSGBM object
*
* rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
* zero. In the current implementation, this parameter must be divisible by 16.
* somewhere in the 3..11 range.
* 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).
* disparity check. Set it to a non-positive value to disable the check.
* 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.
* value should "win" the second best value to consider the found match correct. Normally, a value
* within the 5-15 range is good enough.
* and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
* 50-200 range.
* filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
* Normally, 1 or 2 is good enough.
* 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.
* @return automatically generated
*/
public static StereoSGBM create() {
return StereoSGBM.__fromPtr__(create_11());
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: int cv::StereoSGBM::getPreFilterCap()
private static native int getPreFilterCap_0(long nativeObj);
// C++: void cv::StereoSGBM::setPreFilterCap(int preFilterCap)
private static native void setPreFilterCap_0(long nativeObj, int preFilterCap);
// C++: int cv::StereoSGBM::getUniquenessRatio()
private static native int getUniquenessRatio_0(long nativeObj);
// C++: void cv::StereoSGBM::setUniquenessRatio(int uniquenessRatio)
private static native void setUniquenessRatio_0(long nativeObj, int uniquenessRatio);
// C++: int cv::StereoSGBM::getP1()
private static native int getP1_0(long nativeObj);
// C++: void cv::StereoSGBM::setP1(int P1)
private static native void setP1_0(long nativeObj, int P1);
// C++: int cv::StereoSGBM::getP2()
private static native int getP2_0(long nativeObj);
// C++: void cv::StereoSGBM::setP2(int P2)
private static native void setP2_0(long nativeObj, int P2);
// C++: int cv::StereoSGBM::getMode()
private static native int getMode_0(long nativeObj);
// C++: void cv::StereoSGBM::setMode(int mode)
private static native void setMode_0(long nativeObj, int mode);
// C++: static Ptr_StereoSGBM cv::StereoSGBM::create(int minDisparity = 0, int numDisparities = 16, int blockSize = 3, int P1 = 0, int P2 = 0, int disp12MaxDiff = 0, int preFilterCap = 0, int uniquenessRatio = 0, int speckleWindowSize = 0, int speckleRange = 0, int mode = StereoSGBM::MODE_SGBM)
private static native long create_0(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize, int speckleRange, int mode);
private static native long create_1(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize, int speckleRange);
private static native long create_2(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize);
private static native long create_3(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio);
private static native long create_4(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff, int preFilterCap);
private static native long create_5(int minDisparity, int numDisparities, int blockSize, int P1, int P2, int disp12MaxDiff);
private static native long create_6(int minDisparity, int numDisparities, int blockSize, int P1, int P2);
private static native long create_7(int minDisparity, int numDisparities, int blockSize, int P1);
private static native long create_8(int minDisparity, int numDisparities, int blockSize);
private static native long create_9(int minDisparity, int numDisparities);
private static native long create_10(int minDisparity);
private static native long create_11();
// native support for java finalize()
private static native void delete(long nativeObj);
}
