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Maintenance on Tuesday 15.4. at 14:00. ETA 60 - 90 minutes.
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Nicolas Pope
ftl
Commits
ee5b86d3
Commit
ee5b86d3
authored
4 years ago
by
Nicolas Pope
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parent
774e5a68
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1 merge request
!347
Feature buckets experiment
Pipeline
#26732
failed
4 years ago
Stage: all
Changes
2
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1
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2 changed files
lib/libstereo/src/algorithms/clustersf.cu
+5
-2
5 additions, 2 deletions
lib/libstereo/src/algorithms/clustersf.cu
lib/libstereo/src/filters/focal_cluster.hpp
+2
-1
2 additions, 1 deletion
lib/libstereo/src/filters/focal_cluster.hpp
with
7 additions
and
3 deletions
lib/libstereo/src/algorithms/clustersf.cu
+
5
−
2
View file @
ee5b86d3
...
@@ -84,8 +84,11 @@ void StereoCSF::compute(cv::InputArray l, cv::InputArray r, cv::OutputArray disp
...
@@ -84,8 +84,11 @@ void StereoCSF::compute(cv::InputArray l, cv::InputArray r, cv::OutputArray disp
disp_array
.
toGpuMat
().
download
(
disparity
);
disp_array
.
toGpuMat
().
download
(
disparity
);
cv
::
Mat
gradtmp
;
cv
::
Mat
gradtmp
;
impl_
->
gl
.
toGpuMat
().
download
(
gradtmp
);
conf_array
.
toGpuMat
().
download
(
gradtmp
);
cv
::
imshow
(
"Gradient Left"
,
gradtmp
);
gradtmp
.
convertTo
(
gradtmp
,
CV_8UC1
,
255.0
);
cv
::
applyColorMap
(
gradtmp
,
gradtmp
,
cv
::
COLORMAP_INFERNO
);
cv
::
resize
(
gradtmp
,
gradtmp
,
cv
::
Size
(
gradtmp
.
cols
/
2
,
gradtmp
.
rows
/
2
));
cv
::
imshow
(
"Confidence"
,
gradtmp
);
cv
::
Mat
tmp
;
cv
::
Mat
tmp
;
impl_
->
focal
.
toGpuMat
().
download
(
tmp
);
impl_
->
focal
.
toGpuMat
().
download
(
tmp
);
...
...
This diff is collapsed.
Click to expand it.
lib/libstereo/src/filters/focal_cluster.hpp
+
2
−
1
View file @
ee5b86d3
...
@@ -75,7 +75,8 @@ struct FocalSelector {
...
@@ -75,7 +75,8 @@ struct FocalSelector {
}
}
if
(
max_v
>
0
)
{
if
(
max_v
>
0
)
{
float
conf
=
1.0
f
-
(
float
(
abs
(
best_disp
-
focal_disp
))
/
float
(
max_disparity
));
//float conf = 1.0f - min(1.0f, float(abs(best_disp-focal_disp)) / 10.0f);
float
conf
=
1.0
f
-
min
(
1.0
f
,
float
(
abs
(
distx
))
/
500.0
f
);
if
(
conf
>
confidence
(
y
,
feature
.
x
))
{
if
(
conf
>
confidence
(
y
,
feature
.
x
))
{
disparity
(
y
,
feature
.
x
)
=
float
(
best_disp
);
disparity
(
y
,
feature
.
x
)
=
float
(
best_disp
);
confidence
(
y
,
feature
.
x
)
=
conf
;
confidence
(
y
,
feature
.
x
)
=
conf
;
...
...
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