原文地址： http://answers.opencv.org/question/160599/img-img1mask-img21-mask-how-do-that/
如何提高一个简单操作的速度？最后的 multiply方法很有启示。
Hello,
I would like merge two color images with an image mask.
img1 and img2 are color image with 3 channelsmask is grey image with 1 channel
for merge the two image with the mask I do a loop for each pixel.
float c1,c2;
for(
int j
=
0; j
< img1.rows ; j
++ ){
for(
int i
=
0; i
< img1.cols ; i
++ ){
c1
= (greyGoodScale.at
<uchar
>(j, i))
/
255.
0;
c2
=
1
-c1;
img.at
<Vec3b
>(j, i)[
0]
= c2
*img1.at
<Vec3b
>(j, i)[
0]
+ c1
*img2.at
<Vec3b
>(j, i)[
0];
img.at
<Vec3b
>(j, i)[
1]
= c2
*img1.at
<Vec3b
>(j, i)[
1]
+ c1
*img2.at
<Vec3b
>(j, i)[
1];
img.at
<Vec3b
>(j, i)[
2]
= c2
*img1.at
<Vec3b
>(j, i)[
2]
+ c1
*img2.at
<Vec3b
>(j, i)[
2];
}
}
OK, it's work but my image is 720x500 and i have 70ms of processing time is TOO LONG, I need to be real time.I can't do process on GPU.
Is a way to reduce processing time ?
thank.christopheopenCV 3.x
有用的回答：
1
const uchar
*scale
=
&greyGoodScale.at
<uchar
>(j,
0);
uchar
*imgdata
=
&img.at
<uchar
>(j,
0);
const uchar
*imgdata1
=
&img1.at
<uchar
>(j,
0);
const uchar
*imgdata2
=
&img2.at
<uchar
>(j,
0);
for(
int i
=
0; i
< img1.cols ; i
++ ){
c1
= scale[i]
/
255.
0;
c2
=
1
-c1;
int pos
=
3
*i;
for (
int k
=
0; k
<
3; k
++){
imgdata[pos
+ k]
= c2
*imgdata1[pos
+ k]
+ c1
*imgdata2[pos
+ k];
}
}
is one a the best solution with 16ms of processing time.
Now I would like divide the loop into 4 threads. My code is ok :
std
:
:thread t1(firstQuarter...
..
std
:
:thread t4(fourthQuarter...
t1.join;
...
t4.join;
but time is exactly same of one thread even time is upper.It's just classic access array memory and for the out image they don't need mutex because each thread have a quarter aof the image. How free array matrix for multithread for this easy case ?
2
Mat img1
= imread(
"f:/lib/opencv/samples/data/lena.jpg", IMREAD_COLOR);
Mat img2
= imread(
"f:/lib/opencv/samples/data/orange.jpg", IMREAD_COLOR);
Mat img3,img4;
Mat mask1(img1.rows, img1.cols, CV_8UC1, Scalar(
0));
circle(mask1, Point(
200,
200),
100, Scalar(
92),
-
1);
Mat mask2
=
255
-mask1;
Mat mask2c,mask1c;
vector
<Mat
> pMask
= { mask1,mask1,mask1 };
merge(pMask, mask1c);
pMask.clear();
pMask.push_back(mask2);
pMask.push_back(mask2);
pMask.push_back(mask2);
merge(pMask, mask2c);
multiply(img1, mask1c, img3,
1.
0
/
255, CV_32F);
multiply(img2, mask2c, img4,
1.
0
/
255, CV_32F);
img4
=img3
+img4;
img4.convertTo(img3,CV_8U);
imshow(
"test", img3);
waitKey();
