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Updated stereo block matching approach (when Stereo/OpticalFlow=false)

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matlabbe
2018-11-13 14:25:21 -05:00
parent 227f8c4f86
commit 9efd7c14fc
2 changed files with 67 additions and 57 deletions
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40
tools/StereoEval/main.cpp
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@@ -304,7 +304,6 @@ int main(int argc, char * argv[])
int inliers = 0;
int subInliers = 0;
int badInliers = 0;
int outliers = 0;
float sumInliers = 0.0f;
float sumSubInliers = 0.0f;
int goodRejected = 0;
@@ -366,26 +365,37 @@ int main(int argc, char * argv[])
cv::Point2f(leftCorners[i].x - (d<gt?d:gt), leftCorners[i].y),
cv::Point2f(leftCorners[i].x - (d>gt?d:gt), leftCorners[i].y),
cv::Scalar( 0, 0, 255 ));
++outliers;
++badInliers;
//UDEBUG("should be rejected: %d", i);
}
}
else
{
++badInliers;
}
}
else if(mask.at<cv::Vec3b>(int(rightCorners[i].y), int(leftCorners[i].x))[0] == 255 &&
rightCorners[i].x > 0.0f)
{
float d = leftCorners[i].x - rightCorners[i].x;
cv::line(left,
leftCorners[i],
cv::Point2f(leftCorners[i].x - gt, leftCorners[i].y),
cv::Scalar( 0, 255, 255 ));
if(fabs(d-gt) < 1.0f)
{
cv::line(left,
leftCorners[i],
cv::Point2f(leftCorners[i].x - gt, leftCorners[i].y),
cv::Scalar( 0, 255, 255 ));
cv::line(left,
cv::Point2f(leftCorners[i].x - (d<gt?d:gt), leftCorners[i].y),
cv::Point2f(leftCorners[i].x - (d>gt?d:gt), leftCorners[i].y),
cv::Scalar( 0, 0, 255 ));
++goodRejected;
//UDEBUG("should not be rejected: %d", i);
cv::line(left,
cv::Point2f(leftCorners[i].x - (d<gt?d:gt), leftCorners[i].y),
cv::Point2f(leftCorners[i].x - (d>gt?d:gt), leftCorners[i].y),
cv::Scalar( 0, 0, 255 ));
++goodRejected;
//UDEBUG("should not be rejected: %d", i);
}
else
{
++badRejected;
}
}
else
{
@@ -394,15 +404,11 @@ int main(int argc, char * argv[])
}
}
UINFO("inliers=%d (%d%%) subInliers=%d (%d%%) bad inliers=%d (%d%%) bad accepted=%d (%d%%) good rejected=%d (%d%%) bad rejected=%d (%d%%)",
UINFO("good accepted=%d (%d%%) bad accepted=%d (%d%%) good rejected=%d (%d%%) bad rejected=%d (%d%%)",
inliers,
(inliers*100)/leftCorners.size(),
subInliers,
(subInliers*100)/leftCorners.size(),
badInliers,
(badInliers*100)/leftCorners.size(),
outliers,
(outliers*100)/leftCorners.size(),
goodRejected,
(goodRejected*100)/leftCorners.size(),
badRejected,