[Beignet] [PATCH] Added ocl facedetection demo
Richard Zhang
richardzhangrui1990 at gmail.com
Wed May 29 00:09:48 PDT 2013
Signed-off-by: Richard Zhang <richardzhangrui1990 at gmail.com>
---
demo/oclfacedetection/README | 38 +
demo/oclfacedetection/cl/ccl.cl | 211 ++++
demo/oclfacedetection/cl/imageProcess.cl | 232 ++++
demo/oclfacedetection/cl/kernel_all.cl | 5 +
demo/oclfacedetection/cl/mouthAndEye.cl | 126 +++
demo/oclfacedetection/cl/templateMatch.cl | 127 +++
demo/oclfacedetection/pics/1.jpg | Bin 0 -> 4745 bytes
demo/oclfacedetection/pics/10.jpg | Bin 0 -> 85533 bytes
demo/oclfacedetection/pics/2.jpg | Bin 0 -> 6816 bytes
demo/oclfacedetection/pics/3.jpg | Bin 0 -> 6269 bytes
demo/oclfacedetection/pics/4.jpg | Bin 0 -> 33720 bytes
demo/oclfacedetection/pics/5.jpg | Bin 0 -> 77766 bytes
demo/oclfacedetection/pics/6.jpg | Bin 0 -> 23689 bytes
demo/oclfacedetection/pics/7.jpg | Bin 0 -> 19754 bytes
demo/oclfacedetection/pics/8.jpg | Bin 0 -> 39621 bytes
demo/oclfacedetection/pics/9.jpg | Bin 0 -> 131187 bytes
demo/oclfacedetection/src/common.h | 126 +++
demo/oclfacedetection/src/faceDetect.cpp | 1735 +++++++++++++++++++++++++++++
18 files changed, 2600 insertions(+)
create mode 100644 demo/oclfacedetection/README
create mode 100644 demo/oclfacedetection/cl/ccl.cl
create mode 100644 demo/oclfacedetection/cl/imageProcess.cl
create mode 100644 demo/oclfacedetection/cl/kernel_all.cl
create mode 100644 demo/oclfacedetection/cl/mouthAndEye.cl
create mode 100644 demo/oclfacedetection/cl/templateMatch.cl
create mode 100644 demo/oclfacedetection/pics/1.jpg
create mode 100644 demo/oclfacedetection/pics/10.jpg
create mode 100644 demo/oclfacedetection/pics/2.jpg
create mode 100644 demo/oclfacedetection/pics/3.jpg
create mode 100644 demo/oclfacedetection/pics/4.jpg
create mode 100644 demo/oclfacedetection/pics/5.jpg
create mode 100644 demo/oclfacedetection/pics/6.jpg
create mode 100644 demo/oclfacedetection/pics/7.jpg
create mode 100644 demo/oclfacedetection/pics/8.jpg
create mode 100644 demo/oclfacedetection/pics/9.jpg
create mode 100644 demo/oclfacedetection/src/common.h
create mode 100644 demo/oclfacedetection/src/faceDetect.cpp
diff --git a/demo/oclfacedetection/README b/demo/oclfacedetection/README
new file mode 100644
index 0000000..138e1e2
--- /dev/null
+++ b/demo/oclfacedetection/README
@@ -0,0 +1,38 @@
+Overview:
+
+This software is used to detect human faces in static images and camera captures.
+Now the camera part is far from robust due to various reasons. Meanwhile, the image part also needs to be improved in several aspects.
+Currently, this app only works fine in situations that faces are frontal and easy to see clearly(which means no other things hide the face). Another problem is that faces of some races or in special light conditions will make this app not work fine. And the template match algorithm is not mature also.
+This is only a demo so users can just use the images in the pics folder which the result maybe pleasing.
+
+P.S. The preprocessing phase(extract the skin-like color components) should be improved.
+-----------------
+
+Dependency:
+
+In order to compile this software, there should be some other extra libs pre-installed.
+These libs are:
+1.libopencv-core-dev*
+2.libopencl(any kind of version)
+Because this software is developed to be the example of the Beignet OpenCL driver, the Beignet driver is recommeded. However, other OpenCL drivers still work in appropriate environments.
+-----------------
+
+How to compile:
+
+command:
+first set the BEIGNET_PATH environment by "export BEIGNET_PATH=the_path_of_your_beignet"
+then:
+1.make all: produce the binary
+2.make clean: remove the produced binary
+-----------------
+
+How to run:
+
+./face CAM/input_image_name
+
+The first mode is for camera captures while the second is for static images.
+
+Problems you may encounter when running this software if you use the Beignet driver:
+"error while loading shared libraries: libcl.so: cannot open shared object file: No such file or directory"
+How to solve: export LD_LIBRARY_PATH=the_path_the_libcl.so_reside
+
diff --git a/demo/oclfacedetection/cl/ccl.cl b/demo/oclfacedetection/cl/ccl.cl
new file mode 100644
index 0000000..ab47e6b
--- /dev/null
+++ b/demo/oclfacedetection/cl/ccl.cl
@@ -0,0 +1,211 @@
+//component connected labeling's opencl implementation
+
+#define THRESHOLD 0
+#define MAXINT 2147483647
+
+#define SIZE_THRES 2000
+
+
+/* for binary image connection check
+ * To check whether values of the two dots comforms the condition of connecting
+ */
+bool connected(uint a,uint b)
+{
+ //for special purpose, only wanna find white area
+ return (a == b && a == 255);
+}
+
+/* init lable, references and modified buffers */
+__kernel void init(uint width,uint height, __global uint* labels, __global uint* references, __global uint* modified)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+ if(x >= width || y>= height)
+ {
+ return;
+ }
+ labels[y*width+x] = y*width+x;
+ references[y*width+x] = y*width+x;
+}
+
+/* To scan the point's neighbouring points' pixels and update its own reference */
+__kernel void scan4(const __global uint *image, uint width, uint height, __global uint *labels, __global uint* references, __global uint* modified)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ uint current = labels[y * width + x];
+ uint label = MAXINT;
+
+ uint src = image[y * width + x] & 255;
+
+ if(y-1 >= 0)
+ {
+ uint upsrc = image[(y-1)*width + x] & 255;
+ if(connected(upsrc,src))
+ label = min(label,labels[(y-1)*width + x]);
+ }
+ if(y+1 < height)
+ {
+ uint downsrc = image[(y+1)*width + x] & 255;
+ if(connected(downsrc,src))
+ label = min(label,labels[(y+1)*width + x]);
+ }
+ if(x-1 >= 0)
+ {
+ uint leftsrc = image[y*width + x - 1] & 255;
+ if(connected(leftsrc,src))
+ label = min(label,labels[y*width + x - 1]);
+ }
+ if(x+1 < width)
+ {
+ uint rightsrc = image[y*width + x + 1] & 255;
+ if(connected(rightsrc,src))
+ label = min(label,labels[y*width + x + 1]);
+ }
+ if(label < current)
+ {
+ references[current] = min(references[current],label);
+ //atomic_min(references+current,label);
+ *modified = 1;
+ }
+}
+
+//__kernel void scan8(const __global uint *image, uint width, uint height, __global uint *labels, __global uint* references, __global uint* modified)
+
+/* To update the reference value to its according the reference chain*/
+__kernel void analyse(__global uint *labels, __global uint *references, uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ uint ref = 0;
+ if(labels[y*width+x] == y*width+x)
+ {
+ ref = references[y*width+x];
+ while(ref != references[ref])
+ {
+ ref = references[ref];
+ }
+ references[y*width+x] = ref;
+ }
+}
+
+/* To update the labels according to its references */
+__kernel void label(__global uint *labels, const __global uint *references, uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ labels[y*width+x] = references[labels[y*width+x]];
+}
+
+/* To initialize the area's left,right,top,bottom,size buffer */
+__kernel void init_area(int width,int height, __global int* left,
+ __global int* right, __global int* top, __global int* bottom, __global uint* sz)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+ if(x>=width || y>= height)
+ return;
+
+ left[y*width+x] = MAXINT;
+ right[y*width+x] = 0;
+ top[y*width+x] = MAXINT;
+ bottom[y*width+x] = 0;
+ sz[y*width+x] = 0;
+}
+
+/* update the right,left,top,bottom information */
+__kernel void calAreas(__global uint *labels, __global int* left,
+ __global int* right, __global int* top, __global int* bottom, __global uint *sz, uint width, uint height, __global int* modified)
+{
+ const uint x = get_global_id(0);
+ const uint y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ uint offset = labels[y*width+x];
+
+ if(x < left[offset])
+ {
+ left[offset] = x;
+ modified[0] = 1;
+ }
+ if(x > right[offset])
+ {
+ right[offset] = x;
+ modified[0] = 1;
+ }
+ if(y < top[offset])
+ {
+ top[offset] = y;
+ modified[0] = 1;
+ }
+ if(y > bottom[offset])
+ {
+ bottom[offset] = y;
+ modified[0] = 1;
+ }
+
+ //atomic_add(sz+offset,1);
+ //atomic_min(left+offset,x);
+ //atomic_max(right+offset,x);
+ //atomic_min(top+offset,y);
+ //atomic_max(bottom+offset,y);
+}
+
+/* compute the area size */
+__kernel void calSize( __global int* left,
+ __global int* right, __global int* top, __global int* bottom, __global uint *sz, uint width, uint height)
+
+{
+ const uint x = get_global_id(0);
+ const uint y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ //if(left[y*width + x] == MAXINT || right[y*width +x] == 0 || top[y*width + x] == MAXINT || bottom[y*width +x] == 0)
+ //sz[y*width +x] = 0;
+
+ //else
+ sz[y*width +x] = (right[y*width+x]-left[y*width+x])*(bottom[y*width+x]-top[y*width+x]);
+}
+
+/* update the label information */
+__kernel void updateLabel(__global uint* labels, uint sid, uint lid, uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if ( x >= width || y >= height)
+ return;
+
+ if(labels[y*width+x] == lid)
+ labels[y*width+x] = sid;
+}
+
+
+/* not used */
+__kernel void mergeAreas(__global uint *largeIds, __global uint* left,
+ __global uint* right, __global uint* top, __global uint* bottom, __global uint *sz, uint count)
+{
+ const uint x = get_global_id(0);
+
+ if(x>=count)
+ return;
+
+
+
+}
diff --git a/demo/oclfacedetection/cl/imageProcess.cl b/demo/oclfacedetection/cl/imageProcess.cl
new file mode 100644
index 0000000..27e47ba
--- /dev/null
+++ b/demo/oclfacedetection/cl/imageProcess.cl
@@ -0,0 +1,232 @@
+/* To get the gray value of a certain color */
+uchar gray(uint c)
+{
+ int R = c >> 16 & 255;
+ int G = c >> 8 & 255;
+ int B = c & 255;
+
+ uchar newvalue = convert_uchar_sat((float)B * 0.144f + (float)G * 0.587f + (float)R * 0.299f);
+ return newvalue;
+}
+
+/* get the Y value of YCbCr Space according to rgb values */
+float rgb2Y(int B,int G,int R)
+{
+ float y = 16.0f + 65.738f*(float)R/256.0f + 129.057f*(float)G/256.0f + 25.064f*(float)B/256.0f;
+ //float y = 16.0f + 65.738f*R/256.0f + 129.057f*G/256.0f + 25.064f*B/256.0f;
+ return y;
+ //return 0.299f * (float)R + 0.587f * (float)G + 0.114f * (float)B;
+}
+
+/* get the Cb value of YCbCr Space according to rgb values */
+float rgb2Cb(int B,int G,int R)
+{
+ //float cr = 128.0f + 112.439f*R/256.0f - 94.154f*G/256.0f - 18.285f*B/256.0f;
+ //return cr;
+ float cb = -0.169f * (float)R - 0.332f * (float)G + 0.500f * (float)B;
+ //float cb = -0.169f * R - 0.332f * G + 0.500f * B;
+ return cb;
+}
+
+/* get the Cr value of YCbCr Space according to rgb values */
+float rgb2Cr(int B,int G,int R)
+{
+ //float cb = 128.0f - 37.945f*R/256.0f - 74.494f*G/256.0f + 112.439f*B/256.0f;
+ //return cb;
+
+ float cr = 0.500f * (float)R - 0.419f * (float)G - 0.081f * (float)B;
+ //float cr = 0.500f * R - 0.419f * G - 0.081f * B;
+ return cr;
+}
+
+/* get the R value of RGB Space according to YCbCr values */
+uchar YCbCr2R(float Y,float Cr,float Cb)
+{
+ return convert_uchar_sat(Y + 1.402f * (Cr -128.0f));
+}
+
+/* get the G value of RGB Space according to YCbCr values */
+uchar YCbCr2G(float Y,float Cr,float Cb)
+{
+ return convert_uchar_sat(Y - 0.34414f * (Cb- 128.0f) - 0.71414f * (Cr - 128.0f));
+}
+
+/* get the B value of RGB Space according to YCbCr values */
+uchar YCbCr2B(float Y,float Cr,float Cb)
+{
+ return convert_uchar_sat(Y + 1.772f * (Cb- 128.0f));
+}
+
+/* To change the input rgb values to YCbCr space and set the output buffer
+ * according to the max,min value of Cr,Cb
+ */
+kernel void YCbCrbin(global uint *in, global uint *out, const int width,float maxCr,float minCr,float maxCb,float minCb)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = in[y*width + x];
+ int B = src & 255;
+ int G = src >> 8 & 255;
+ int R = src >> 16 & 255;
+ int A = src >> 24 & 255;
+
+ float b = (float)B/255.0f;
+ float g = (float)G/255.0f;
+ float r = (float)R/255.0f;
+
+ float Y = rgb2Y(B,G,R);
+ float Cr = rgb2Cr(B,G,R);
+ float Cb = rgb2Cb(B,G,R);
+
+ //float Y = rgb2Y(b,g,r);
+ //float Cr = rgb2Cr(b,g,r);
+ //float Cb = rgb2Cb(b,g,r);
+
+ if(Cb <= maxCb && Cb >= minCb)
+ Cb = 1.0f;
+ else
+ Cb = 0.0f;
+ if(Cr <= maxCr && Cr >= minCr)
+ Cr = 1.0f;
+ else
+ Cr = 0.0f;
+
+ //uchar gv = (uchar)Cb;
+ uchar gv = 255 * Cr * Cb;
+
+ //R = YCbCr2R(Y,Cr,Cb);
+ //G = YCbCr2G(Y,Cr,Cb);
+ //B = YCbCr2B(Y,Cr,Cb);
+
+ out[y * width + x] = (A << 24) + (gv << 16) + (gv << 8) + gv;
+ //out[y * width + x] = gv;
+}
+
+/* To change the input image memory buffer to gray value memory buffer */
+kernel void grayImage(global uint *in, global uint *out, const int width)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = in[y*width + x];
+ int B = src & 255;
+ int G = src >> 8 & 255;
+ int R = src >> 16 & 255;
+ int A = src >> 24 & 255;
+
+ src = B + (G << 8) + (R << 16) + (A << 24);
+ uchar g = gray(src);
+ out[y * width + x] = (A << 24) + (g << 16) + (g << 8) + g;
+
+}
+
+/* To get the edge of the input image using roberts operator */
+kernel void roberts(const global uint *in, global uint *out, const global int *m1, const global int *m2,const int width,const int height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = in[y*width + x];
+ int gx = 0,gy = 0;
+ for(int k = 0;k <= 1;k++)
+ for(int l = 0;l <=1; l++)
+ {
+ if(y+k>=0&&y+k<height&&x+l>=0&&x+l<width)
+ {
+ gx += (int)(in[width*(y+k) + (l+x)] & 255)*m1[k*2+l];
+ gy += (int)(in[width*(y+k) + (l+x)] & 255)*m2[k*2+l];
+ }
+ }
+ uchar g = convert_uchar_sat(sqrt((float)(gx*gx + gy*gy)));
+ //uchar g = convert_uchar_sat(gx+gy);
+ out[y * width + x] = (src & (255 << 24)) + (g << 16) + (g << 8) + g;
+}
+
+/* To get the edges of the input image using sobel operator */
+kernel void sobel(const global uint *in, global uint *out, const global int *m1, const global int *m2,const int width,const int height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = in[y*width + x];
+ int gx = 0,gy = 0;
+ for(int k = -1;k <= 1;k++)
+ for(int l = -1;l <=1; l++)
+ {
+ if(y+k>=0&&y+k<height&&x+l>=0&&x+l<width)
+ {
+ gx += (int)(in[width*(y+k) + (l+x)] & 255)*m1[(k+1)*3+l+1];
+ gy += (int)(in[width*(y+k) + (l+x)] & 255)*m2[(k+1)*3+l+1];
+ }
+ }
+ uchar g = convert_uchar_sat(sqrt((float)(gx*gx + gy*gy)));
+ //uchar g = convert_uchar_sat(gx+gy);
+ out[y * width + x] = (src & (255 << 24)) + (g << 16) + (g << 8) + g;
+}
+
+/* To segregate the input image using edges previously obtained */
+kernel void segmentImage(const global uint* edge,global uint *out,const int w)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = edge[y * w + x];
+ uint b = src & 255;
+ uint g = (src >>8) & 255;
+ uint r = (src >> 16) & 255;
+ if(b > 20 || g > 20 || r > 20)
+ out[y * w + x] = 0;
+}
+
+/* To pose an erosion operation on the given image with the radius ra */
+kernel void erodeImage(const global uint *in, global uint *out, const int ra, const int w, const int h) {
+
+ const int cx = get_global_id(0);
+ const int cy = get_global_id(1);
+ uint r = 255, g = 255, b = 255, a = 255;
+ for(int y = cy - ra; y <= cy + ra; y ++)
+ for(int x = cx - ra; x <= cx + ra; x ++)
+ if(0 <= x && x < w && 0 <= y && y < h) {
+ uint c = in[y * w + x];
+ a = min(a, (c >> 24) & 255);
+ r = min(r, (c >> 16) & 255);
+ g = min(g, (c >> 8) & 255);
+ b = min(b, c & 255);
+ }
+ out[cy * w + cx] = (a << 24)|(r << 16)|(g << 8)|b;
+ }
+
+
+
+/* To pose a dilation operation on the given image with given radius ra */
+ kernel void dilateImage(const global uint *in, global uint *out, const int ra, const int w, const int h) {
+
+ const int cx = get_global_id(0);
+ const int cy = get_global_id(1);
+ uint r = 0, g = 0, b = 0, a = 0;
+ for(int y = cy - ra; y <= cy + ra; y ++)
+ for(int x = cx - ra; x <= cx + ra; x ++)
+ if(0 <= x && x < w && 0 <= y && y < h) {
+ uint c = in[y * w + x];
+ a = max(a, (c >> 24) & 255);
+ r = max(r, (c >> 16) & 255);
+ g = max(g, (c >> 8) & 255);
+ b = max(b, c & 255);
+ }
+
+ out[cy * w + cx] = (a << 24)|(r << 16)|(g << 8)|b;
+ }
+
+/* test function,not used */
+__kernel void testconversion(const global uint *in, global uint *out,uint width)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ uint src = in[y*width + x];
+
+ float s = src;
+
+ out[y*width +x] = s;
+}
diff --git a/demo/oclfacedetection/cl/kernel_all.cl b/demo/oclfacedetection/cl/kernel_all.cl
new file mode 100644
index 0000000..5749588
--- /dev/null
+++ b/demo/oclfacedetection/cl/kernel_all.cl
@@ -0,0 +1,5 @@
+// add all the cl files
+
+#include "imageProcess.cl"
+#include "ccl.cl"
+#include "templateMatch.cl"
diff --git a/demo/oclfacedetection/cl/mouthAndEye.cl b/demo/oclfacedetection/cl/mouthAndEye.cl
new file mode 100644
index 0000000..db9198b
--- /dev/null
+++ b/demo/oclfacedetection/cl/mouthAndEye.cl
@@ -0,0 +1,126 @@
+
+// TODO: Add OpenCL kernel code here.
+
+__kernel void extractColorFace(__global uint* in, __global uint* out,
+ uint iwidth, uint iheight, uint owidth, uint oheight,
+ int left,int top)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= owidth || y>= oheight)
+ return;
+
+ out[y*owidth+x] = in[(top+y)*iwidth+(left+x)];
+}
+
+__kernel void grayDilation(__global uint *in, __global uint *out, __global float *gvalues, uint width, uint height, uint sigma)
+{
+ const int cx = get_global_id(0);
+ const int cy = get_global_id(1);
+ uint r = 0, g = 0, b = 0, a = 0;
+ for(int y = cy - sigma; y <= cy + sigma; y ++)
+ for(int x = cx - sigma; x <= cx + sigma; x ++)
+ {
+ int six = x - cx + sigma;
+ int siy = y - cy + sigma;
+ if(0 <= x && x < width && 0 <= y && y < height && (pow(y - cy,2.0f) + pow (x - cx ,2.0f) <= pow(sigma ,2.0f))) {
+ uint c = (float)(in[y * width + x] &255) + gvalues[(sigma * 2 - siy) * (2 * sigma + 1) + (sigma * 2 - six)];
+ c = c > 255?255:(c<0?0:c);
+ //a = max(a, (c >> 24) & 255);
+ //r = max(r, (c >> 16) & 255);
+ //g = max(g, (c >> 8) & 255);
+ b = max(b, c & 255);
+ }
+ }
+
+ out[cy * width + cx] = (b << 24)|(b << 16)|(b << 8)|b;
+}
+
+__kernel void grayErosion(__global uint *in, __global uint *out, __global float *gvalues, uint width, uint height, uint sigma)
+{
+ const int cx = get_global_id(0);
+ const int cy = get_global_id(1);
+ uint r = 255, g = 255, b = 255, a = 255;
+ for(int y = cy - sigma; y <= cy + sigma; y ++)
+ for(int x = cx - sigma; x <= cx + sigma; x ++)
+ {
+ int six = x - cx + sigma;
+ int siy = y - cy + sigma;
+ if(0 <= x && x < width && 0 <= y && y < height && (pow(y - cy,2.f) + pow (x - cx ,2.f) <= pow(sigma ,2.f))) {
+ uint c = (float)(in[y * width + x] &255) - gvalues[siy * (2 * sigma + 1) + six];
+ c = c > 255?255:(c<0?0:c);
+ //a = max(a, (c >> 24) & 255);
+ //r = max(r, (c >> 16) & 255);
+ //g = max(g, (c >> 8) & 255);
+ b = min(b, c & 255);
+ }
+ }
+
+ out[cy * width + cx] = (b << 24)|(b << 16)|(b << 8)|b;
+}
+
+__kernel void getYImage(__global uint *in, __global uint *out, uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ uint src = in[y * width + x];
+ int B = src & 255;
+ int G = src >> 8 & 255;
+ int R = src >> 16 & 255;
+ int A = src >> 24 & 255;
+
+ //float Y = 16.0 + 65.738*(float)R/256.0 + 129.057*(float)G/256.0 + 25.064*(float)B/256.0;
+
+ float Y = 0.299f * (float)R + 0.587f * (float)G + 0.114f * (float)B;
+
+ uint v = (uint)Y & 255;
+
+ out[y * width + x] = (v << 24)|(v << 16)|(v << 8)|v;
+}
+
+__kernel void extractEye(__global uint *in, __global uint *out, __global uint *dilateSrc, __global uint *erodeSrc,
+ uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ uint src = in[y * width + x];
+ int B = src & 255;
+ int G = src >> 8 & 255;
+ int R = src >> 16 & 255;
+ int A = src >> 24 & 255;
+
+ float Cr = 0.500f * (float)R - 0.419f * (float)G - 0.081f * (float)B;
+ float Cb = -0.169f * (float)R - 0.332f * (float)G + 0.500f * (float)B;
+
+ //float Cb = 128.0 - 37.945*(float)R/256.0 - 74.494*(float)G/256.0 + 112.439*(float)B/256.0;
+ //float Cr = 128.0 + 112.439*(float)R/256.0 - 94.154*(float)G/256.0 - 18.285*(float)B/256.0;
+
+ int EyeMapC = 0.333f * (Cb * Cb / 255.0f + (255.0f - Cr) * (255.0f - Cr) / 255.0f + Cb/Cr*255.0f);
+
+ //int EyeMapC = (255 - (int)Cr) * (255 -(int)Cr);
+
+ //int EyeMapC = ((int)Cb * (int)Cb) / 255;
+
+ EyeMapC = EyeMapC & 255;
+
+ int dValue = dilateSrc[y * width + x] & 255;
+ int eValue = erodeSrc[y * width + x] & 255;
+
+ int EyeMapL = ((float)dValue/(float)(eValue + 1)) * 255.0f;
+
+ int newValue = EyeMapC & EyeMapL & 255;
+
+ //out[ y * width +x ] = (255 << 24)|(EyeMapC << 16)|(EyeMapC << 8)|EyeMapC;
+
+ out[ y * width +x ] = (newValue << 24)|(newValue << 16)|(newValue << 8)|newValue;
+
+}
diff --git a/demo/oclfacedetection/cl/templateMatch.cl b/demo/oclfacedetection/cl/templateMatch.cl
new file mode 100644
index 0000000..00c8bf5
--- /dev/null
+++ b/demo/oclfacedetection/cl/templateMatch.cl
@@ -0,0 +1,127 @@
+//the opencl template match implementation
+
+/* To reshape a given image using nearest principle, not used in this app */
+__kernel void reshape(const global uint *in, global uint *out,
+ const int iWidth, const int iHeight, const int oWidth, const int oHeight)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ float wscale = (float)iWidth/(float)oWidth;
+ float hscale = (float)iHeight/(float)oHeight;
+
+ int ix = (int)(x * wscale);
+ int iy = (int)(y * hscale);
+
+ if(ix >= iWidth || iy >= iHeight)
+ return;
+
+ uint src = in[iy * iWidth + ix];
+
+ int B = src & 255;
+ int G = src >> 8 & 255;
+ int R = src >> 16 & 255;
+ int A = src >> 24 & 255;
+
+ out[y * oWidth + x] = (A << 24) + (R << 16) + (G << 8) + B;
+}
+
+/* extract faces given a certain area and certain labelid, not used in this app */
+__kernel void extractFaces(__global uint* in, __global uint* out, __global uint* label, uint id,
+ uint iwidth, uint iheight, uint owidth, uint oheight,
+ int left,int top)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= owidth || y>= oheight)
+ return;
+
+ if(label[(top+y)*iwidth+(left+x)] == id)
+ out[y*owidth+x] = in[(top+y)*iwidth+(left+x)];
+ else
+ out[y*owidth+x] = 0;
+}
+
+/* To compare a certain image with a certain template, not used in this app */
+__kernel void templateMatch(__global uint* in, __global uint* temp,
+ uint width,uint height,__global uint* scores)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ int src = in[y*width+x] & 255;
+ int b = temp[y*width+x] & 255;
+ int g = (temp[y*width+x] >> 8) & 255;
+ int r = (temp[y*width+x] >> 16) & 255;
+ int v = (b+g+r)/3;
+
+ src *= v/255;
+ if(src > 200)
+ //if(src == 255 && v > 128)
+ //atomic_add(scores,1);
+ scores[0] += 1;
+}
+
+/* extract the whole area given */
+__kernel void ColorFace(__global uint *in, __global uint* out,
+ uint iwidth, uint iheight,uint owidth, uint oheight,
+ int left,int top)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= owidth || y>= oheight)
+ return;
+
+ out[y*owidth+x] = in[(top+y)*iwidth+(left+x)];
+
+}
+
+/* To check the given area's pixels which meet certain condition and compute the final score */
+__kernel void checkSpecialPart(__global uint *in, __global uint *labels, uint width, uint height,
+ float xsProportion, float xeProportion, float ysProportion, float yeProportion)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ if(x >= width || y >= height)
+ return;
+
+ float fx = (float)x;
+ float fy = (float)y;
+
+ if(fx < (float)width * xsProportion || fx >= (float)width * xeProportion || fy < (float)height * ysProportion || fy > (float)height * yeProportion)
+ {
+ labels[y*width + x] = 0;
+ return;
+ }
+
+ int src = in[y*width+x];
+ int b = src & 255;
+ int g = (src >> 8) & 255;
+ int r = (src >> 16) & 255;
+ int v = (b+g+r)/3;
+
+ if(v > 10)
+ labels[y*width + x] = 1;
+ else
+ labels[y*width + x] = 0;
+}
+
+/* not used in this app */
+__kernel void addScore(__global uint *labels, uint width, uint height)
+{
+ const int x = get_global_id(0);
+ const int y = get_global_id(1);
+
+ for(int stride = width * height/2; stride > 0; stride /= 2)
+ {
+ if(y*width+x+stride >= width*height)
+ continue;
+ labels[y*width+x] += labels[y*width+x+stride];
+ }
+}
diff --git a/demo/oclfacedetection/pics/1.jpg b/demo/oclfacedetection/pics/1.jpg
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diff --git a/demo/oclfacedetection/pics/10.jpg b/demo/oclfacedetection/pics/10.jpg
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diff --git a/demo/oclfacedetection/src/common.h b/demo/oclfacedetection/src/common.h
new file mode 100644
index 0000000..a403774
--- /dev/null
+++ b/demo/oclfacedetection/src/common.h
@@ -0,0 +1,126 @@
+#ifndef COMMON_H
+#define COMMON_H
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+using namespace cv;
+
+int max(int a,int b, int c)
+{
+ return a>b?(a>c?a:c):(b>c?b:c);
+}
+
+int min(int a,int b,int c)
+{
+ return a<b?(a<c?a:c):(b<c?b:c);
+}
+
+double changeToH(int r,int g,int b,int max,int min)
+{
+ if(max == min)
+ return 0.0;
+ else if(r == max && g>=b)
+ return 60.0*((double)(g-b))/((double)(max-min));
+ else if(r == max && g<b)
+ return 60.0*((double)(g-b))/((double)(max-min))+360.0;
+ else if(g == max)
+ return 60.0*((double)(b-r))/((double)(max-min))+120.0;
+ else if(b == max)
+ return 60.0*((double)(r-g))/((double)(max-min))+120.0;
+}
+
+double changeToL(int max,int min)
+{
+ return (double)(max+min)/2.0;
+}
+
+double changeToS(int r,int g,int b,int max,int min,double l)
+{
+ if(max == min || l == 0.0)
+ return 0.0;
+ else if(0.0<l && l<=0.5)
+ return (double)(max-min)/(2.0*l);
+ else if(l>0.5)
+ return (double)(max-min)/(2.0 - 2.0*l);
+
+
+}
+
+int fillMargin(int number,const int object)
+{
+ int tmp = (number + object - 1)/object * object;
+ return tmp;
+}
+
+void fillAlphaChannel(Mat& image,int channels)
+{
+ if(channels == 4)
+ return;
+ else
+ {
+ for(int i=0;i<image.rows;i++)
+ {
+ for(int j=3;j<image.cols*4;j=j+4)
+ {
+ image.data[image.step * i + j] = 255;
+ }
+ }
+ }
+}
+
+void changeTo4C(Mat& i1)
+{
+ Mat i2 = Mat(i1.rows,i1.cols,CV_8UC4);
+ int from_to[8];
+ if(i1.channels() == 1)
+ {
+ from_to[0] = 0;
+ from_to[1] = 0;
+ from_to[2] = 0;
+ from_to[3] = 1;
+ from_to[4] = 0;
+ from_to[5] = 2;
+ from_to[6] = 0;
+ from_to[7] = 3;
+ mixChannels(&i1,1,&i2,1,from_to,4);
+ fillAlphaChannel(i2,1);
+ i1 = i2;
+ }
+ else if(i1.channels() == 3)
+ {
+ from_to[0] = 0;
+ from_to[1] = 0;
+ from_to[2] = 1;
+ from_to[3] = 1;
+ from_to[4] = 2;
+ from_to[5] = 2;
+ from_to[6] = 0;
+ from_to[7] = 3;
+ mixChannels(&i1,1,&i2,1,from_to,4);
+ fillAlphaChannel(i2,3);
+ i1 = i2;
+ }
+}
+
+inline int readChannel(const Mat& image, const int posX,const int posY, const int number)
+{
+ return image.data[posY * image.step + posX * 4 + number];
+}
+
+inline int changeToY(int r, int g, int b)
+{
+ return 0.299 * (double)r + 0.587 * (double)g + 0.114 * (double)b;
+}
+
+inline int changeToCb(int r, int g, int b)
+{
+ return -0.169 * (double)r - 0.332 * (double)g + 0.500 * (double)b;
+}
+
+inline int changeToCr(int r, int g, int b)
+{
+ return 0.500 * (double)r - 0.419 * (double)g - 0.081 * (double)b;
+}
+
+#endif
diff --git a/demo/oclfacedetection/src/faceDetect.cpp b/demo/oclfacedetection/src/faceDetect.cpp
new file mode 100644
index 0000000..7237e9c
--- /dev/null
+++ b/demo/oclfacedetection/src/faceDetect.cpp
@@ -0,0 +1,1735 @@
+#include <iostream>
+#include <stdio.h>
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+//#include <sys/time.h>
+#include <cmath>
+
+#include <CL/cl.h>
+
+#include "common.h"
+
+using namespace std;
+using namespace cv;
+
+#define MAXINT 0x7fffffff
+//threhold of large connected area size
+#define THRES_SIZE 2000
+
+//horizontal and vertical distance threshold to merge two nearby connected areas
+#define HTAG 10
+#define VTAG 30
+
+//range of eyes and mouth
+#define EYE_TOP 0.195
+#define EYE_BOTTOM 0.4
+#define LEFT_EYE_LEFT 0.15
+#define LEFT_EYE_RIGHT 0.45
+#define RIGHT_EYE_LEFT 0.55
+#define RIGHT_EYE_RIGHT 0.85
+#define MOUTH_TOP 0.45
+#define MOUTH_BOTTOM 0.72
+#define MOUTH_LEFT 0.25
+#define MOUTH_RIGHT 0.7
+
+//cl source path
+const char *PROG_SOURCE = "cl/kernel_all.cl";
+cl_int err;
+
+//workgroup dimension and size
+cl_uint work_dim = 2;
+const int LOCAL_GROUP_WIDTH = 16;
+const int LOCAL_GROUP_HEIGHT = 16;
+
+//cl parameters
+cl_platform_id x_platform;
+cl_device_id x_device;
+cl_context x_context;
+cl_command_queue x_cmd_q;
+cl_program x_prog;
+size_t prog_length;
+
+#define check(err) assert(err == CL_SUCCESS)
+typedef unsigned int uint;
+
+/* cFilename: name of loading file
+ * cPreamble: string before load
+ * szFinalLength: string length after load
+ * return: string after load
+ * To get the file content as a string
+ */
+char* oclLoadProgSource(const char* cFilename, const char* cPreamble, size_t* szFinalLength)
+{
+ // locals
+ FILE* pFileStream = NULL;
+ size_t szSourceLength;
+
+ // open the OpenCL source code file
+ #ifdef _WIN32 // Windows version
+ if(fopen_s(&pFileStream, cFilename, "rb") != 0)
+ {
+ return NULL;
+ }
+ #else // Linux version
+ pFileStream = fopen(cFilename, "rb");
+ if(pFileStream == 0)
+ {
+ return NULL;
+ }
+ #endif
+
+ size_t szPreambleLength = strlen(cPreamble);
+
+ // get the length of the source code
+ fseek(pFileStream, 0, SEEK_END);
+ szSourceLength = ftell(pFileStream);
+ fseek(pFileStream, 0, SEEK_SET);
+
+ // allocate a buffer for the source code string and read it in
+ char* cSourceString = (char *)malloc(szSourceLength + szPreambleLength + 1);
+ memcpy(cSourceString, cPreamble, szPreambleLength);
+ if (fread((cSourceString) + szPreambleLength, szSourceLength, 1, pFileStream) != 1)
+ {
+ fclose(pFileStream);
+ free(cSourceString);
+ return 0;
+ }
+
+ // close the file and return the total length of the combined (preamble + source) string
+ fclose(pFileStream);
+ if(szFinalLength != 0)
+ {
+ *szFinalLength = szSourceLength + szPreambleLength;
+ }
+ cSourceString[szSourceLength + szPreambleLength] = '\0';
+
+ return cSourceString;
+}
+
+/* To initialize OpenCL relevant parameters */
+void setupCL()
+{
+ err = clGetPlatformIDs(1, &x_platform, NULL);
+ check(err);
+ //err = clGetDeviceIDs(x_platform,CL_DEVICE_TYPE_GPU, 1, &x_device, NULL);
+ //check(err);
+ x_context = clCreateContext(NULL, 1, &x_device, NULL,NULL,&err);
+ if(err != 0)
+ {
+ err = clGetDeviceIDs(x_platform, CL_DEVICE_TYPE_GPU, 1, &x_device, NULL);
+ check(err);
+ x_context = clCreateContext(NULL,1, &x_device, NULL,NULL,&err);
+ check(err);
+ }
+ x_cmd_q = clCreateCommandQueue(x_context, x_device, 0, &err);
+ check(err);
+ char *source = oclLoadProgSource(PROG_SOURCE,"",&prog_length);
+ x_prog = clCreateProgramWithSource(x_context, 1, (const char**)&source, &prog_length, &err);
+ check(err);
+ err = clBuildProgram(x_prog, 1, &x_device, "-I cl",NULL,NULL);
+ //log
+ if(err == CL_BUILD_PROGRAM_FAILURE){
+ size_t log_size;
+ clGetProgramBuildInfo(x_prog,x_device,CL_PROGRAM_BUILD_LOG,0,NULL,&log_size);
+ char *log = (char*) malloc(log_size);
+ clGetProgramBuildInfo(x_prog,x_device,CL_PROGRAM_BUILD_LOG,log_size,log,NULL);
+ cout<<log<<endl;
+ }
+ //log end
+ check(err);
+}
+
+/* in: memory buffer of input image
+ * out: memory buffer of output image
+ * tmp: input image
+ * To process the input image and get the skin-like color components
+ */
+void get_face_color(cl_mem &in,cl_mem &out,Mat &tmp)
+{
+
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ /*cout<<owidth<<" "<<oheight<<endl;
+ cout<<ow<<" "<<oh<<endl;*/
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel reshape_kernel = clCreateKernel(x_prog,"YCbCrbin",&err);
+ check(err);
+ in = clCreateBuffer(x_context, CL_MEM_READ_ONLY, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+ out = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ float meanY = 161.9964;
+ float meanCb = -11.1051;
+ float meanCr = 22.9265;
+ float stdY = 25.9997;
+ float stdCb = 4.3568;
+ float stdCr = 3.9479;
+ float factor = 2.0;
+ //-11.4798 22.8043 5.65622 7.19236
+ //float meanY = 161.9964;
+ //float meanCb = -11.4798;
+ //float meanCr = 22.8043;
+ //float stdY = 25.9997;
+ //float stdCb = 5.65622;
+ //float stdCr = 7.19236;
+ //float factor = 2.0;
+
+ float min_Cb=meanCb-stdCb*factor;
+ float max_Cb=meanCb+stdCb*factor;
+ float min_Cr=meanCr-stdCr*factor;
+ float max_Cr=meanCr+stdCr*factor;
+
+
+ err = clSetKernelArg(reshape_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 2, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 3, sizeof(max_Cr), &max_Cr);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 4, sizeof(min_Cr), &min_Cr);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 5, sizeof(max_Cb), &max_Cb);
+ check(err);
+ err = clSetKernelArg(reshape_kernel, 6, sizeof(min_Cb), &min_Cb);
+ check(err);
+ err = clEnqueueWriteBuffer(x_cmd_q, in, CL_TRUE,
+ 0, tmp.cols*tmp.rows*sizeof(uint), tmp.data, 0, NULL,NULL);
+
+ check(err);
+
+ //run
+ err = clEnqueueNDRangeKernel(x_cmd_q, reshape_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(reshape_kernel);
+ //cout<<"1.no error";
+}
+
+/* in: memory buffer of input image
+ * out: memory buffer of output image
+ * tmp: input image
+ * To get edges using roberts operator
+ */
+void roberts(cl_mem &in,cl_mem &out,Mat &tmp)
+{
+ cl_mem m1,m2;
+
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel roberts_kernel = clCreateKernel(x_prog, "roberts",&err);
+ check(err);
+
+ out = clCreateBuffer(x_context, CL_MEM_READ_WRITE, owidth * oheight * sizeof(uint), NULL, &err);
+ check(err);
+ m1 = clCreateBuffer(x_context, CL_MEM_READ_ONLY, 4*sizeof(int), NULL, &err);
+ check(err);
+ m2 = clCreateBuffer(x_context, CL_MEM_READ_ONLY, 4*sizeof(int), NULL, &err);
+ check(err);
+
+ err = clSetKernelArg(roberts_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(roberts_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(roberts_kernel, 2, sizeof(m1), &m1);
+ check(err);
+ err = clSetKernelArg(roberts_kernel, 3, sizeof(m2), &m2);
+ check(err);
+ err = clSetKernelArg(roberts_kernel, 4, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(roberts_kernel, 5, sizeof(oheight), &oheight);
+ check(err);
+
+ int m1_in[] = {1,0,0,-1};
+ int m2_in[] = {0,1,-1,0};
+ err = clEnqueueWriteBuffer(x_cmd_q, m1, CL_TRUE,
+ 0, 4*sizeof(int), m1_in, 0, NULL,NULL);
+ check(err);
+ err = clEnqueueWriteBuffer(x_cmd_q, m2, CL_TRUE,
+ 0, 4*sizeof(int), m2_in, 0, NULL,NULL);
+ check(err);
+
+ //run
+ err = clEnqueueNDRangeKernel(x_cmd_q, roberts_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(roberts_kernel);
+ clReleaseMemObject(m1);
+ clReleaseMemObject(m2);
+ //cout<<"3.no error";
+}
+
+/* in: memory buffer of input image
+ * out:memory buffer of output image
+ * tmp:input image
+ * To get edges using sobel operator
+ */
+void sobel(cl_mem &in,cl_mem &out,Mat &tmp)
+{
+ cl_mem m1,m2;
+
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel sobel_kernel = clCreateKernel(x_prog, "sobel",&err);
+ check(err);
+
+ out = clCreateBuffer(x_context, CL_MEM_READ_WRITE, owidth * oheight * sizeof(uint), NULL, &err);
+ check(err);
+ m1 = clCreateBuffer(x_context, CL_MEM_READ_ONLY, 9*sizeof(int), NULL, &err);
+ check(err);
+ m2 = clCreateBuffer(x_context, CL_MEM_READ_ONLY, 9*sizeof(int), NULL, &err);
+ check(err);
+
+ err = clSetKernelArg(sobel_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(sobel_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(sobel_kernel, 2, sizeof(m1), &m1);
+ check(err);
+ err = clSetKernelArg(sobel_kernel, 3, sizeof(m2), &m2);
+ check(err);
+ err = clSetKernelArg(sobel_kernel, 4, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(sobel_kernel, 5, sizeof(oheight), &oheight);
+ check(err);
+
+ int m1_in[] = {-1,0,1,-2,0,2,-1,0,1};
+ int m2_in[] = {-1,-2,-1,0,0,0,1,2,1};
+ err = clEnqueueWriteBuffer(x_cmd_q, m1, CL_TRUE,
+ 0, 9*sizeof(int), m1_in, 0, NULL,NULL);
+ check(err);
+ err = clEnqueueWriteBuffer(x_cmd_q, m2, CL_TRUE,
+ 0, 9*sizeof(int), m2_in, 0, NULL,NULL);
+ check(err);
+
+ //run
+ err = clEnqueueNDRangeKernel(x_cmd_q, sobel_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(sobel_kernel);
+ clReleaseMemObject(m1);
+ clReleaseMemObject(m2);
+ //cout<<"3.no error";
+}
+
+/* image: input image
+ * image_mem: memory buffer of input image
+ * width: output width
+ * height:output_height
+ * left: the x coordinate of the leftmost point
+ * top: the y coordinate of the topmost point
+ * score1: left eye area score
+ * score2: right eye area score
+ * score3: mouth area score
+ * To check and compute the proportion of eyes and mouth areas' pixels exceeding certain threshold
+ */
+void check_special_part(Mat& image, cl_mem &image_mem,
+ int width, int height, int left, int top, int &score1, int &score2, int &score3)
+{
+ int iw = image.cols;
+ int ih = image.rows;
+
+ int ow = fillMargin(width,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(height,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel extract_kernel = clCreateKernel(x_prog,"ColorFace",&err);
+ check(err);
+ cl_kernel label_kernel = clCreateKernel(x_prog,"checkSpecialPart",&err);
+ check(err);
+ cl_kernel cal_kernel = clCreateKernel(x_prog,"addScore",&err);
+
+ cl_mem in = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ cl_mem score_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ err = clSetKernelArg(extract_kernel, 0, sizeof(image_mem), &image_mem);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 1, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 2, sizeof(iw), &iw);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 3, sizeof(ih), &ih);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 4, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 5, sizeof(height), &height);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 6, sizeof(left), &left);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 7, sizeof(top), &top);
+ check(err);
+
+ float xsProportion = LEFT_EYE_LEFT;
+ float xeProportion = LEFT_EYE_RIGHT;
+ float ysProportion = EYE_TOP;
+ float yeProportion = EYE_BOTTOM;
+
+ err = clSetKernelArg(label_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(label_kernel, 1, sizeof(score_mem), &score_mem);
+ check(err);
+ err = clSetKernelArg(label_kernel, 2, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(label_kernel, 3, sizeof(height), &height);
+ check(err);
+ err = clSetKernelArg(label_kernel, 4, sizeof(xsProportion), &xsProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 5, sizeof(xeProportion), &xeProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 6, sizeof(ysProportion), &ysProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 7, sizeof(yeProportion), &yeProportion);
+ check(err);
+
+ err = clSetKernelArg(cal_kernel, 0, sizeof(score_mem), &score_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 1, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 2, sizeof(height), &height);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, extract_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, label_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //err = clEnqueueNDRangeKernel(x_cmd_q, cal_kernel, work_dim,
+ //NULL,
+ //gws,
+ //lws,
+ //0,
+ //NULL,
+ //NULL
+ //);
+ //check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(extract_kernel);
+ //clReleaseKernel(label_kernel);
+
+ uint *xxx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ score_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ width*height*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ int sum = 0;
+ for(int i=0;i<width*height;i++)
+ sum += xxx[i];
+ //cout<<"score1: "<<sum<<endl;
+ score1 = sum;
+
+ //for(int i=0;i<width*height;i++)
+ //if(xxx[i] != 0)
+ //cout<<i<<": "<<xxx[i]<<endl;
+
+ xsProportion = RIGHT_EYE_LEFT;
+ xeProportion = RIGHT_EYE_RIGHT;
+ //int ysProportion = EYE_TOP;
+ //int yeProportion = EYE_BOTTOM;
+
+ err = clSetKernelArg(label_kernel, 4, sizeof(xsProportion), &xsProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 5, sizeof(xeProportion), &xeProportion);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, label_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //err = clEnqueueNDRangeKernel(x_cmd_q, cal_kernel, work_dim,
+ //NULL,
+ //gws,
+ //lws,
+ //0,
+ //NULL,
+ //NULL
+ //);
+ //check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ xxx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ score_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ width*height*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ sum = 0;
+ for(int i=0;i<width*height;i++)
+ sum += xxx[i];
+
+ //cout<<"score2: "<<sum<<endl;
+ score2 = sum;
+
+ xsProportion = MOUTH_LEFT;
+ xeProportion = MOUTH_RIGHT;
+ ysProportion = MOUTH_TOP;
+ yeProportion = MOUTH_BOTTOM;
+
+ err = clSetKernelArg(label_kernel, 4, sizeof(xsProportion), &xsProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 5, sizeof(xeProportion), &xeProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 6, sizeof(ysProportion), &ysProportion);
+ check(err);
+ err = clSetKernelArg(label_kernel, 7, sizeof(yeProportion), &yeProportion);
+ check(err);
+
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, label_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //err = clEnqueueNDRangeKernel(x_cmd_q, cal_kernel, work_dim,
+ //NULL,
+ //gws,
+ //lws,
+ //0,
+ //NULL,
+ //NULL
+ //);
+ //check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ xxx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ score_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ width*height*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ sum = 0;
+ for(int i=0;i<width*height;i++)
+ sum += xxx[i];
+ //cout<<"score3: "<<sum<<endl;
+
+ score3 = sum;
+
+ //Mat temp = Mat(width,height,CV_8UC4);
+
+
+ //uint* xxx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ // in,
+ // CL_TRUE,
+ // 0,
+ // 0,
+ // width*height*sizeof(uint),
+ // 0,
+ // NULL,
+ // NULL,
+ // &err);
+ //check(err);
+ //err = clFinish(x_cmd_q);
+ //check(err);
+
+ //Mat res = Mat(height,width,CV_8UC4);
+ //memcpy(res.data, xxx, width*height*sizeof(uint));
+ //char name[1000];
+ //sprintf(name,"face%d.bmp",left+top);
+ //imwrite(name,res);
+
+ clReleaseMemObject(in);
+ clReleaseMemObject(score_mem);
+
+}
+
+/* in: memory buffer of input image
+ * out:memroy buffer of output image
+ * tmp:input image
+ * ra: erosion radius
+ * To make an erosion operation on the given image with the radius ra
+ */
+void erode(cl_mem &in, cl_mem &out,Mat &tmp,int ra)
+{
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel erode_kernel = clCreateKernel(x_prog,"erodeImage",&err);
+ check(err);
+
+ out = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ err = clSetKernelArg(erode_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(erode_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(erode_kernel, 2, sizeof(ra), &ra);
+ check(err);
+ err = clSetKernelArg(erode_kernel, 3, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(erode_kernel, 4, sizeof(oheight), &oheight);
+ check(err);
+
+ //run
+ err = clEnqueueNDRangeKernel(x_cmd_q, erode_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(erode_kernel);
+ //cout<<"3.no error";
+}
+
+/* in: memory buffer of input image
+ * out:memroy buffer of output image
+ * tmp:input image
+ * ra: dilation radius
+ * To make an dilation operation on the given image with the radius ra
+ */
+void dilate(cl_mem &in,cl_mem &out,Mat &tmp,int ra)
+{
+
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel dilate_kernel = clCreateKernel(x_prog,"dilateImage",&err);
+ check(err);
+
+ out = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ err = clSetKernelArg(dilate_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(dilate_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(dilate_kernel, 2, sizeof(ra), &ra);
+ check(err);
+ err = clSetKernelArg(dilate_kernel, 3, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(dilate_kernel, 4, sizeof(oheight), &oheight);
+ check(err);
+
+ //run
+ err = clEnqueueNDRangeKernel(x_cmd_q, dilate_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(dilate_kernel);
+ //cout<<"2.no error";
+}
+
+/* in: memory buffer of input image
+ * out: memory buffer of output image
+ * tmp: input image
+ * To segregate nearby connected areas(faces) using edges previously gained
+ */
+void segImage(cl_mem& in,cl_mem& out,Mat& tmp)
+{
+ int owidth = tmp.cols;
+ int oheight = tmp.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel seg_kernel = clCreateKernel(x_prog,"segmentImage",&err);
+ check(err);
+
+ err = clSetKernelArg(seg_kernel, 0, sizeof(in), &in);
+ check(err);
+ err = clSetKernelArg(seg_kernel, 1, sizeof(out), &out);
+ check(err);
+ err = clSetKernelArg(seg_kernel, 2, sizeof(owidth), &owidth);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, seg_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ clReleaseKernel(seg_kernel);
+}
+
+/* label_mem: connected componets label memory buffer
+ * sid: the new id(small)
+ * lid: the old id(large)
+ * image: the input image
+ * To update the old ids to new ids
+ * This function is previously used but not used in the app curently
+ */
+void updateLabel(cl_mem& label_mem,uint sid, uint lid, Mat image)
+{
+ int owidth = image.cols;
+ int oheight = image.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_kernel update_kernel;
+
+ update_kernel = clCreateKernel(x_prog,"updateLabel",&err);
+ check(err);
+
+ //update function set args
+ err = clSetKernelArg(update_kernel, 0, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(update_kernel, 1, sizeof(sid), &sid);
+ check(err);
+ err = clSetKernelArg(update_kernel, 2, sizeof(lid), &lid);
+ check(err);
+ err = clSetKernelArg(update_kernel, 3, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(update_kernel, 4, sizeof(oheight), &oheight);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, update_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ clReleaseKernel(update_kernel);
+}
+
+/* label_mem: connected components label memory buffer
+ * image: the input image
+ * image_mem: memory buffer of the input image
+ * To find connected area, every pixel in one connected area has the same label id
+ */
+void findConnectedComponent(cl_mem& label_mem,Mat& image, cl_mem& image_mem)
+{
+ int owidth = image.cols;
+ int oheight = image.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ cl_mem ref_mem,modified_mem;
+
+ cl_kernel init_kernel, scan_kernel, anal_kernel, label_kernel;
+
+ uint *modified = new uint;
+ *modified = 1;
+
+ init_kernel = clCreateKernel(x_prog,"init",&err);
+ check(err);
+ scan_kernel = clCreateKernel(x_prog,"scan4",&err);
+ check(err);
+ anal_kernel = clCreateKernel(x_prog,"analyse",&err);
+ check(err);
+ label_kernel = clCreateKernel(x_prog,"label",&err);
+ check(err);
+
+ label_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ ref_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ modified_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, sizeof(uint), NULL, &err);
+ check(err);
+
+ //init function set args
+ err = clSetKernelArg(init_kernel, 0, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(init_kernel, 1, sizeof(oheight), &oheight);
+ check(err);
+ err = clSetKernelArg(init_kernel, 2, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 3, sizeof(ref_mem), &ref_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 4, sizeof(modified_mem), &modified_mem);
+ check(err);
+
+ //scan function set args
+ err = clSetKernelArg(scan_kernel, 0, sizeof(image_mem), &image_mem);
+ check(err);
+ err = clSetKernelArg(scan_kernel, 1, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(scan_kernel, 2, sizeof(oheight), &oheight);
+ check(err);
+ err = clSetKernelArg(scan_kernel, 3, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(scan_kernel, 4, sizeof(ref_mem), &ref_mem);
+ check(err);
+ err = clSetKernelArg(scan_kernel, 5, sizeof(modified_mem), &modified_mem);
+ check(err);
+
+ //analysis function set args
+ err = clSetKernelArg(anal_kernel, 0, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(anal_kernel, 1, sizeof(ref_mem), &ref_mem);
+ check(err);
+ err = clSetKernelArg(anal_kernel, 2, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(anal_kernel, 3, sizeof(oheight), &oheight);
+ check(err);
+
+ //analysis function set args
+ err = clSetKernelArg(label_kernel, 0, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(label_kernel, 1, sizeof(ref_mem), &ref_mem);
+ check(err);
+ err = clSetKernelArg(label_kernel, 2, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(label_kernel, 3, sizeof(oheight), &oheight);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, init_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ while(*modified == 1)
+ {
+ *modified = 0;
+ //scan
+ err = clEnqueueNDRangeKernel(x_cmd_q, scan_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //analyse
+ err = clEnqueueNDRangeKernel(x_cmd_q, anal_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //label
+ err = clEnqueueNDRangeKernel(x_cmd_q, label_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ //retrieve modified flag
+ modified = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ modified_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ }
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ clReleaseKernel(init_kernel);
+ clReleaseKernel(scan_kernel);
+ clReleaseKernel(anal_kernel);
+ clReleaseKernel(label_kernel);
+ clReleaseMemObject(ref_mem);
+ clReleaseMemObject(modified_mem);
+
+}
+
+/* label_mem: connected area memory buffer
+ * left_mem: connected area leftmost points coordinates memory buffer
+ * right_mem: connected area rightmost points coordinates memory buffer
+ * top_mem: connected area topmost points coordinates memroy buffer
+ * bottom_mem: connected area bottommost points coordinates memory buffer
+ * sz_mem: connected area size memory buffer
+ * image: input image
+ * To calculate every connected area's size, leftmost, rightmost, topmost and bottommost points coordinates
+ */
+void extractLarge(cl_mem &label_mem, cl_mem &left_mem, cl_mem &right_mem, cl_mem &top_mem, cl_mem &bottom_mem, cl_mem &sz_mem, Mat &image)
+{
+ int owidth = image.cols;
+ int oheight = image.rows;
+ int ow = fillMargin(owidth,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(oheight,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ uint *modified = new uint;
+ *modified = 1;
+
+ cl_mem modified_mem;
+
+ cl_kernel init_kernel = clCreateKernel(x_prog,"init_area",&err);
+ check(err);
+ cl_kernel cal_kernel = clCreateKernel(x_prog,"calAreas",&err);
+ check(err);
+ cl_kernel cal_size_kernel = clCreateKernel(x_prog,"calSize",&err);
+ check(err);
+
+ modified_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, sizeof(int), NULL, &err);
+ check(err);
+
+ left_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(int), NULL, &err);
+ check(err);
+
+ right_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(int), NULL, &err);
+ check(err);
+
+ top_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(int), NULL, &err);
+ check(err);
+
+ bottom_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(int), NULL, &err);
+ check(err);
+
+ sz_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+
+ //cal function set args
+ err = clSetKernelArg(cal_kernel, 0, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 1, sizeof(left_mem), &left_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 2, sizeof(right_mem), &right_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 3, sizeof(top_mem), &top_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 4, sizeof(bottom_mem), &bottom_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 5, sizeof(sz_mem), &sz_mem);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 6, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 7, sizeof(oheight), &oheight);
+ check(err);
+ err = clSetKernelArg(cal_kernel, 8, sizeof(modified_mem), &modified_mem);
+ check(err);
+
+ //cal size function set args
+ err = clSetKernelArg(cal_size_kernel, 0, sizeof(left_mem), &left_mem);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 1, sizeof(right_mem), &right_mem);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 2, sizeof(top_mem), &top_mem);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 3, sizeof(bottom_mem), &bottom_mem);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 4, sizeof(sz_mem), &sz_mem);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 5, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(cal_size_kernel, 6, sizeof(oheight), &oheight);
+ check(err);
+
+ //init function set args
+ err = clSetKernelArg(init_kernel, 0, sizeof(owidth), &owidth);
+ check(err);
+ err = clSetKernelArg(init_kernel, 1, sizeof(oheight), &oheight);
+ check(err);
+ err = clSetKernelArg(init_kernel, 2, sizeof(left_mem), &left_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 3, sizeof(right_mem), &right_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 4, sizeof(top_mem), &top_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 5, sizeof(bottom_mem), &bottom_mem);
+ check(err);
+ err = clSetKernelArg(init_kernel, 6, sizeof(sz_mem), &sz_mem);
+ check(err);
+
+ uint *size = new uint[owidth*oheight]();
+ err = clEnqueueWriteBuffer(x_cmd_q, sz_mem, CL_TRUE,
+ 0, owidth*oheight*sizeof(uint), size, 0, NULL,NULL);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, init_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ while(*modified == 1)
+ {
+ *modified = 0;
+ err = clEnqueueNDRangeKernel(x_cmd_q, cal_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ //retrieve modified flag
+ modified = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ modified_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ }
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, cal_size_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ delete[] size;
+ clReleaseMemObject(modified_mem);
+ clReleaseKernel(init_kernel);
+ clReleaseKernel(cal_kernel);
+ clReleaseKernel(cal_size_kernel);
+}
+
+/* To compare the input image with the template image and get a score
+ * This function is previously used but not used currently
+ */
+void judge(cl_mem &in_mem, cl_mem &out_mem, cl_mem &tmp_mem, Mat& image, cl_mem &image_mem,
+ int width, int left, int top, cl_mem &score_mem, float &score, cl_mem &label_mem, uint id)
+{
+ int ow = fillMargin(width,LOCAL_GROUP_WIDTH);
+ int oh = fillMargin(width,LOCAL_GROUP_HEIGHT);
+
+ size_t gws[] = {ow, oh};
+ size_t lws[] = {LOCAL_GROUP_WIDTH,LOCAL_GROUP_HEIGHT};
+
+ int w;
+ bool flag = false;
+ for(w = 30;w<240;w+=10)
+ {
+ if(abs(w - width) < 10)
+ {
+ flag = true;
+ break;
+ }
+ }
+ if(!flag)
+ {
+ if(width < 30)
+ w = 30;
+ if(width > 230)
+ w = 230;
+ }
+ else if(abs(w-width) > abs(w-width+10) && w <=220)
+ w = w+10;
+
+ char filename[1000];
+ sprintf(filename,"../templates/template%d.bmp",w);
+
+ cout<<filename<<endl;
+
+ Mat tmp = imread(filename,CV_LOAD_IMAGE_ANYCOLOR);
+
+ changeTo4C(tmp);
+
+ int ow_re = fillMargin(w,LOCAL_GROUP_WIDTH);
+ int oh_re = fillMargin(w,LOCAL_GROUP_HEIGHT);
+
+ size_t gws_re[] = {ow_re, oh_re};
+
+ cl_kernel extract_kernel = clCreateKernel(x_prog,"extractFaces",&err);
+ check(err);
+ cl_kernel shape_kernel = clCreateKernel(x_prog,"reshape",&err);
+ check(err);
+ cl_kernel match_kernel = clCreateKernel(x_prog,"templateMatch",&err);
+ check(err);
+
+ in_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow * oh * sizeof(uint), NULL, &err);
+ check(err);
+ out_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow_re * oh_re * sizeof(uint), NULL, &err);
+ check(err);
+ tmp_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, ow_re * oh_re * sizeof(uint), NULL, &err);
+ check(err);
+ score_mem = clCreateBuffer(x_context, CL_MEM_READ_WRITE, sizeof(uint), NULL, &err);
+ check(err);
+
+ err = clEnqueueWriteBuffer(x_cmd_q, tmp_mem, CL_TRUE,
+ 0, w*w*sizeof(uint), tmp.data, 0, NULL,NULL);
+ check(err);
+
+ uint* score_ptr = new uint;
+ *score_ptr = 0;
+
+ err = clEnqueueWriteBuffer(x_cmd_q, score_mem, CL_TRUE,
+ 0, sizeof(uint), score_ptr, 0, NULL,NULL);
+ check(err);
+
+ //extract function set args
+ err = clSetKernelArg(extract_kernel, 0, sizeof(image_mem), &image_mem);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 1, sizeof(in_mem), &in_mem);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 2, sizeof(label_mem), &label_mem);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 3, sizeof(id), &id);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 4, sizeof(image.cols), &image.cols);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 5, sizeof(image.rows), &image.rows);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 6, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 7, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 8, sizeof(left), &left);
+ check(err);
+ err = clSetKernelArg(extract_kernel, 9, sizeof(top), &top);
+ check(err);
+
+ //reshape function set args
+ err = clSetKernelArg(shape_kernel, 0, sizeof(in_mem), &in_mem);
+ check(err);
+ err = clSetKernelArg(shape_kernel, 1, sizeof(out_mem), &out_mem);
+ check(err);
+ err = clSetKernelArg(shape_kernel, 2, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(shape_kernel, 3, sizeof(width), &width);
+ check(err);
+ err = clSetKernelArg(shape_kernel, 4, sizeof(w), &w);
+ check(err);
+ err = clSetKernelArg(shape_kernel, 5, sizeof(w), &w);
+ check(err);
+
+ //match function set args
+ err = clSetKernelArg(match_kernel, 0, sizeof(out_mem), &out_mem);
+ check(err);
+ err = clSetKernelArg(match_kernel, 1, sizeof(tmp_mem), &tmp_mem);
+ check(err);
+ err = clSetKernelArg(match_kernel, 2, sizeof(w), &w);
+ check(err);
+ err = clSetKernelArg(match_kernel, 3, sizeof(w), &w);
+ check(err);
+ err = clSetKernelArg(match_kernel, 4, sizeof(score_mem), &score_mem);
+ check(err);
+
+ err = clEnqueueNDRangeKernel(x_cmd_q, extract_kernel, work_dim,
+ NULL,
+ gws,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clEnqueueNDRangeKernel(x_cmd_q, shape_kernel, work_dim,
+ NULL,
+ gws_re,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+ err = clEnqueueNDRangeKernel(x_cmd_q, match_kernel, work_dim,
+ NULL,
+ gws_re,
+ lws,
+ 0,
+ NULL,
+ NULL
+ );
+ check(err);
+
+
+ //uint* xxx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ //out_mem,
+ //CL_TRUE,
+ //0,
+ //0,
+ //w*w*sizeof(uint),
+ //0,
+ //NULL,
+ //NULL,
+ //&err);
+ //check(err);
+ //err = clFinish(x_cmd_q);
+ //check(err);
+
+ //Mat res = Mat(w,w,CV_8UC4);
+ //memcpy(res.data, xxx, w*w*sizeof(uint));
+ //char name[1000];
+ //sprintf(name,"face%d.bmp",left+top);
+ //imwrite(name,res);
+
+
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ //retrieve score flag
+ score_ptr = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ score_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ score = (float)(*score_ptr)/(float)(w*w);
+
+ tmp.release();
+ clReleaseMemObject(tmp_mem);
+ clReleaseMemObject(in_mem);
+ clReleaseMemObject(out_mem);
+ clReleaseMemObject(score_mem);
+ clReleaseKernel(extract_kernel);
+ clReleaseKernel(shape_kernel);
+ clReleaseKernel(match_kernel);
+}
+
+/* image: the input iamge
+ * result: the processed image
+ * To process the image to detect face
+ */
+void faceDetect(Mat &image,Mat &result)
+{
+ /* clear the previous processd image */
+ result.release();
+
+ cl_mem in = NULL,out = NULL,dilate_mem = NULL,erode_mem = NULL,sobel_mem = NULL,sobel_erode = NULL;
+ cl_mem di_out = NULL, er_out = NULL, test_out = NULL;
+
+ /* extract skin-color parts */
+ get_face_color(in,out,image);
+ //test_converstion(in,test_out,image);
+
+ /* get the edge of the image */
+ roberts(in,sobel_mem,image);
+
+ /* impose a closing operation on the skin-color extraction output
+ * To eleminate tiny black hole in connected components
+ */
+ dilate(out,erode_mem,image,3);
+ erode(erode_mem,dilate_mem,image,3);
+
+ /* impose an opening operation on the previous result
+ * To eleminate tiny white dot in this image
+ */
+ erode(dilate_mem,erode_mem,image,1);
+ dilate(erode_mem,dilate_mem,image,1);
+
+ /* Use the roberts edge of the image
+ * To segregate different skin-color components of this image
+ */
+ segImage(sobel_mem,dilate_mem,image);
+
+ /* read the middle result after image prcocessing phase */
+ uint *xx = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ dilate_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ image.rows*image.cols*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+ result = Mat(image.rows,image.cols,CV_8UC4);
+ memcpy(result.data, xx, image.rows*image.cols*sizeof(uint));
+
+ //struct timeval tv;
+ //gettimeofday(&tv, NULL);
+ //double begin = (tv.tv_sec) * 1000 + (tv.tv_usec) / 1000 ;
+
+ cl_mem label_mem;
+ /* find connected components of result and store the labels information in label_mem */
+ findConnectedComponent(label_mem,result,dilate_mem);
+
+ cl_mem left_mem,right_mem,top_mem,bottom_mem,sz_mem;
+
+ /* extract large(size greater than a threshold) connected componets information in this image */
+ extractLarge(label_mem,left_mem,right_mem,top_mem,bottom_mem,sz_mem,result);
+
+ int* left = (int *) clEnqueueMapBuffer(x_cmd_q,
+ left_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(int),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+
+ int* right = (int *) clEnqueueMapBuffer(x_cmd_q,
+ right_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(int),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+
+ int* top = (int *) clEnqueueMapBuffer(x_cmd_q,
+ top_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(int),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+
+ int* bottom = (int *) clEnqueueMapBuffer(x_cmd_q,
+ bottom_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(int),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+
+
+ uint *sz = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ sz_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+
+ uint* labels = (uint *) clEnqueueMapBuffer(x_cmd_q,
+ label_mem,
+ CL_TRUE,
+ 0,
+ 0,
+ result.cols*result.rows*sizeof(uint),
+ 0,
+ NULL,
+ NULL,
+ &err);
+ check(err);
+ err = clFinish(x_cmd_q);
+ check(err);
+
+ uint* largeIds= new uint[(image.rows*image.cols+THRES_SIZE-1)/THRES_SIZE];
+
+ /* retrieve the large component ids(label) */
+ int count = 0;
+ for(int i = 0;i<image.rows;i++)
+ {
+ for(int j = 0;j<image.cols;j++)
+ {
+ double ratio = (double)(right[i*image.cols+j] - left[i*image.cols+j]) / (double)(bottom[i*image.cols+j] - top[i*image.cols+j]);
+ bool similar_rec = (ratio <= 2.5) && (ratio >=0.4);
+ if(sz[i*image.cols+j] > THRES_SIZE && similar_rec)
+ {
+ //cout<<i*image.cols+j<<" "<<sz[i*image.cols+j]<<endl;
+ //cout<<left[i*image.cols+j]<<" "<<right[i*image.cols+j]<<" "<<top[i*image.cols+j]<<" "<<bottom[i*image.cols+j]<<endl;
+ largeIds[count] = i*image.cols+j;
+ count++;
+ }
+ }
+ }
+
+ /* merge nearby components that should be one component */
+ for(int i=0;i<count-1;i++)
+ {
+ //cout<<"count in"<<endl;
+ if(sz[largeIds[i]] > 0)
+ {
+
+ for(int j=i;j<count;j++)
+ {
+ bool cd1 = ((abs(top[largeIds[i]] - bottom[largeIds[j]]) < VTAG) || (abs(top[largeIds[j]] - bottom[largeIds[i]]) < VTAG)
+ ||(top[largeIds[i]]>top[largeIds[j]] && top[largeIds[i]]<bottom[largeIds[j]])
+ ||(top[largeIds[j]]>top[largeIds[i]] && top[largeIds[j]]<bottom[largeIds[i]])
+ ||(bottom[largeIds[i]]>top[largeIds[j]] && bottom[largeIds[i]]<bottom[largeIds[j]])
+ ||(bottom[largeIds[j]]>top[largeIds[i]] && bottom[largeIds[j]]<bottom[largeIds[i]]));
+ bool cd2 = ((abs(left[largeIds[i]] - left[largeIds[j]]) < HTAG) || (abs(right[largeIds[i]] - right[largeIds[j]]) < HTAG)
+ || (left[largeIds[i]] > left[largeIds[j]] && right[largeIds[i]] < right[largeIds[j]])
+ || (left[largeIds[j]] > left[largeIds[i]] && right[largeIds[j]] < right[largeIds[i]]));
+ if(sz[largeIds[j]] > 0 && cd1 && cd2)
+ {
+ int s_id = largeIds[i]<largeIds[j]?largeIds[i]:largeIds[j];
+ int l_id = largeIds[i] + largeIds[j] - s_id;
+ //labels[l_id] = s_id;
+
+ updateLabel(label_mem,s_id,l_id,result);
+
+ sz[s_id] += sz[l_id];
+ sz[l_id] = 0;
+ left[s_id] = left[l_id]<left[s_id]?left[l_id]:left[s_id];
+ right[s_id] = right[l_id]>right[s_id]?right[l_id]:right[s_id];
+ top[s_id] = top[l_id]<top[s_id]?top[l_id]:top[s_id];
+ bottom[s_id] = bottom[l_id]>bottom[s_id]?bottom[l_id]:bottom[s_id];
+ j = i-1;
+ }
+ }
+ }
+ }
+
+
+ int large_count = 0;
+
+ /* for every connected component
+ * judge whether it match the basic template
+ * in my function I compute the proportion of white dots in eyes and mouth areas
+ * if the proportion of the three areas all exceed a certain threshold
+ * this component is a face candidate
+ */
+ for(int i=0;i<count;i++)
+ {
+ if(sz[largeIds[i]] > 0)
+ {
+ //cout<<largeIds[i]<<" "<<sz[largeIds[i]]<<" "<<endl;
+ large_count++;
+ int sx = left[largeIds[i]];
+ int sy = top[largeIds[i]];
+ int ex = right[largeIds[i]];
+ int ey = bottom[largeIds[i]];
+ //cout<<sx<<" "<<sy<<" "<<ex<<" "<<ey<<endl;
+
+ int tmp_width,tmp_left,tmp_top;
+ if((ey-sy)>(ex-sx))
+ {
+ tmp_width = ey - sy;
+ tmp_left = (sx + ex - tmp_width)/2;
+ if(tmp_left < 0)
+ tmp_left = 0;
+ if((tmp_left + tmp_width) > result.cols)
+ tmp_left = result.cols - tmp_width;
+ tmp_top = sy;
+ }
+ else
+ {
+ tmp_width = ex - sx;
+ tmp_top = (sy + ey - tmp_width)/2;
+ if(tmp_top < 0)
+ tmp_top = 0;
+ if((tmp_top + tmp_width) > result.rows)
+ tmp_top = result.rows - tmp_width;
+ tmp_left = sx;
+ }
+
+ //cout<<sx<<" "<<sy<<" "<<ex<<" "<<ey<<endl;
+ cl_mem in_mem,out_mem,tmp_mem,score_mem;
+
+ float score = 0.0;
+
+ //judge(in_mem, out_mem, tmp_mem, result, dilate_mem,
+ //tmp_width, tmp_left, tmp_top, score_mem, score, label_mem, largeIds[i]);
+
+ //cl_mem tmp_out = NULL;
+
+ int owidth = ex - sx;
+ int oheight = ey - sy;
+ int score1 = 0;
+ int score2 = 0;
+ int score3 = 0;
+
+ /* check the proportion of special parts: left eye, right eye and mouth */
+ check_special_part(result,sobel_mem,owidth,oheight,left[largeIds[i]],top[largeIds[i]],score1,score2,score3);
+
+ bool left_eye = false,right_eye = false,mouth = false;
+
+ //cout<<owidth<<" "<<oheight<<endl;
+
+ float portion1 = (float)score1/((float)(owidth*oheight)*((LEFT_EYE_RIGHT-LEFT_EYE_LEFT)*(EYE_BOTTOM-EYE_TOP)));
+ float portion2 = (float)score2/((float)(owidth*oheight)*((RIGHT_EYE_RIGHT-RIGHT_EYE_LEFT)*(EYE_BOTTOM-EYE_TOP)));
+ float portion3 = (float)score3/((float)(owidth*oheight)*((MOUTH_RIGHT-MOUTH_LEFT)*(MOUTH_BOTTOM-MOUTH_TOP)));
+
+ //cout<<portion1<<" "<<portion2<<" "<<portion3<<endl;
+
+ if(portion1 > 0.1)
+ left_eye = true;
+ if(portion2 > 0.1)
+ right_eye = true;
+ if(portion3 > 0.1)
+ mouth = true;
+
+ //cout<<score<<endl;
+
+ //rectangle(result,Point(tmp_left,tmp_top),Point(tmp_left+tmp_width,tmp_top+tmp_width),Scalar(0,0,255,255),2);
+
+ if(left_eye && right_eye && mouth )
+ rectangle(image,Point(sx,sy),Point(ex,ey),Scalar(0,0,255,255),2);
+ }
+ }
+
+ /* clean the resources */
+ if(in != NULL)
+ clReleaseMemObject(in);
+ if(out != NULL)
+ clReleaseMemObject(out);
+ if(dilate_mem != NULL)
+ clReleaseMemObject(dilate_mem);
+ if(erode_mem != NULL)
+ clReleaseMemObject(erode_mem);
+ if(sobel_mem != NULL)
+ clReleaseMemObject(sobel_mem);
+ if(label_mem != NULL)
+ clReleaseMemObject(label_mem);
+ if(left_mem != NULL)
+ clReleaseMemObject(left_mem);
+ if(right_mem != NULL)
+ clReleaseMemObject(right_mem);
+ if(top_mem != NULL)
+ clReleaseMemObject(top_mem);
+ if(bottom_mem != NULL)
+ clReleaseMemObject(bottom_mem);
+ if(sz_mem != NULL)
+ clReleaseMemObject(sz_mem);
+
+}
+
+int main(int argc, char** argv)
+{
+
+
+ if(argc != 2)
+ {
+ cout<<"Usage: faceDetect ImageName/CAM"<<endl;
+ return -1;
+ }
+
+ Mat image;
+
+
+ /* init cl relevant parameters */
+ setupCL();
+ /*choose the mode
+ * the camera mode
+ */
+ if(strcmp(argv[1], "CAM") == 0)
+ {
+
+ VideoCapture capture(0);
+ if(!capture.isOpened())
+ {
+ cout<<"Camera not open!"<<endl;
+ return -1;
+ }
+
+ namedWindow("Face Detection",CV_WINDOW_AUTOSIZE);
+
+ while(1)
+ {
+ if(!capture.read(image))
+ {
+ cout<<"Cant read image from camera!"<<endl;
+ break;
+ }
+ changeTo4C(image);
+
+ Mat result;
+ faceDetect(image,result);
+ imshow("Face Detection",result);
+ waitKey(40);
+ // break;
+ }
+ capture.release();
+ }
+ /* the static image mode */
+ else
+ {
+ image = imread(argv[1],CV_LOAD_IMAGE_ANYCOLOR);
+ if(!image.data)
+ {
+ cout<<"Cant open this image!"<<endl;
+ return -1;
+ }
+ changeTo4C(image);
+ Mat result;
+ faceDetect(image,result);
+
+
+ namedWindow("Face Detection",CV_WINDOW_AUTOSIZE);
+ imshow("Face Detection",image);
+ //imwrite("test.bmp",result);
+ waitKey(0);
+ }
+ return 0;
+}
--
1.8.1.2
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