GTK + OPENCV 处理视频并显示

1. Target    = demo_gtk
   
2. 
   
3. SrcDir= .
   
4. ExtList= .cpp .c
   
5. 
   
6. Source= $(foreach ext,$(ExtList), \
   
7.     $(foreach sd, $(SrcDir), $(wildcard $(addprefix $(sd)/*,$(ext)))))
   
8. 
   
9. Objs= $(foreach ext, $(ExtList), \
   
10.     $(patsubst %$(ext), %.o, $(filter %$(ext),$(Source))))
    
11. 
    
12. CFLAGS := -Wall
    
13. LIBS := -lrt -lpthread
    
14. INCDIR := -I . -I /usr/include/publib -I/usr/include/jsoncpp/
    
15. 
    
16. LIBS += -lopencv_core -lopencv_highgui -lopencv_ml -lopencv_imgproc -lopencv_video -lopencv_objdetect
    
17. LIBS += `pkg-config --libs gtk+-2.0`
    
18. INCDIR += -I /usr/include/opencv
    
19. INCDIR += `pkg-config --cflags gtk+-2.0`
    
20. 
    
21. CC=g++
    
22. CPP=g++
    
23. 
    
24. %.o : %.c
    
25.     $(CC) $(CFLAGS) -c $(@D)/$(<F) -o $(@D)/$(@F) $(INCDIR)
    
26. %.o : %.cpp
    
27.     $(CPP) $(CFLAGS) -c $(@D)/$(<F) -o $(@D)/$(@F) $(INCDIR)
    
28. 
    
29. $(Target): $(Objs)
    
30.     $(CC) -o $(Target) $(Objs) $(LIBS)
    
31. 
    
32. all: $(Target)
    
33. 
    
34. objs: $(Objs)
    
35.     
    
36. RM= rm -rf
    
37. 
    
38. clean:
    
39.     @$(RM) $(foreach sd, $(SrcDir), $(wildcard $(sd)/*.o))
    
40.     @$(RM) $(Target)
    
41. 
    
42. cleanall:clean
    
43.     @$(RM) $(Target)
    
44. 
    
45. rebuild: cleanall all

主要为 mat 对象的 RGB值转换的问题.

1. #include <gtk/gtk.h>
   
2. #include <glib/gstdio.h>
   
3. #include <stdio.h>
   
4. 
   
5. 
   
6. #include <opencv2/highgui/highgui.hpp>
   
7. #include <opencv2/imgproc/imgproc.hpp>
   
8. #include <opencv2/core/core.hpp>
   
9. #include <opencv2/objdetect/objdetect.hpp>
   
10. 
    
11. #include <errno.h>
    
12. #include <string>
    
13. using std::string;
    
14. 
    
15. #include <iostream>
    
16. #include <vector>
    
17. #include <sstream>
    
18. using std::stringstream;
    
19. 
    
20. using namespace cv;
    
21. using namespace std;
    
22. 
    
23. int ydi_absname(char *buf, uint bufsiz)
    
24. {
    
25.     int count = readlink( "/proc/self/exe", buf, bufsiz-1 );
    
26.     if (-1 == count)
    
27.         return -errno;
    
28.     
    
29.     buf[ count ] = '\0';
    
30.     return count;
    
31. }
    
32. 
    
33. int ydi_dirname(char *buf, uint bufsiz)
    
34. {
    
35.     int count = ydi_absname(buf, bufsiz);
    
36.     if (count > 0) {
    
37.         do {
    
38.             if (buf[ --count ] == '/') {
    
39.                 buf[ count ] = '\0';
    
40.                 break;
    
41.             }
    
42.         } while (count > 0);
    
43.     }
    
44.     return count;
    
45. }
    
46. 
    
47. static Mat frame;
    
48. static CascadeClassifier cascade, nestedCascade;
    
49. static double scale = 4; //近距离用 4， 远用 6
    
50. 
    
51. int detectAndDraw( Mat& img, CascadeClassifier& cascade, CascadeClassifier& nestedCascade, double scale)
    
52. {
    
53.     int i = 0;
    
54.     double t = 0;
    
55.     //建立用于存放人脸的向量容器
    
56.     vector<Rect> faces, faces2;
    
57. 
    
58.     //定义一些颜色，用来标示不同的人脸
    
59.     //*
    
60.     const static Scalar colors[] = { CV_RGB(0,0,255),
    
61.         CV_RGB(0,128,255),
    
62.         CV_RGB(0,255,255),
    
63.         CV_RGB(0,255,0),
    
64.         CV_RGB(255,128,0),
    
65.         CV_RGB(255,255,0),
    
66.         CV_RGB(255,0,0),
    
67.         CV_RGB(255,0,255)} ;
    
68.     //*/
    
69.     
    
70.     //建立缩小的图片，加快检测速度
    
71.     //nt cvRound (double value) 对一个double型的数进行四舍五入，并返回一个整型数！
    
72.     Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
    
73. 
    
74.     //转成灰度图像，Harr特征基于灰度图
    
75.     cvtColor( img, gray, CV_BGR2GRAY );
    
76.     
    
77.     //改变图像大小，使用双线性差值
    
78.     resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
    
79.     //变换后的图像进行直方图均值化处理
    
80.     equalizeHist( smallImg, smallImg );
    
81. 
    
82.     //程序开始和结束插入此函数获取时间，经过计算求得算法执行时间
    
83.     t = (double)cvGetTickCount();
    
84.     //检测人脸
    
85.     //detectMultiScale函数中smallImg表示的是要检测的输入图像为smallImg，faces表示检测到的人脸目标序列，1.1表示
    
86.     //每次图像尺寸减小的比例为1.1，2表示每一个目标至少要被检测到3次才算是真的目标(因为周围的像素和不同的窗口大
    
87.     //小都可以检测到人脸),CV_HAAR_SCALE_IMAGE表示不是缩放分类器来检测，而是缩放图像，Size(30, 30)为目标的
    
88.     //最小最大尺寸
    
89.     cascade.detectMultiScale( smallImg, faces,
    
90.         1.1, 2, 0
    
91.         //|CV_HAAR_FIND_BIGGEST_OBJECT
    
92.         //|CV_HAAR_DO_ROUGH_SEARCH
    
93.         |CV_HAAR_SCALE_IMAGE
    
94.         ,
    
95.         Size(30, 30));
    
96. 
    
97.     Mat smallImgROI;
    
98.     vector<Rect> nestedObjects;
    
99.     Point center;
    
100.     int radius;
     
101.     
     
102.     for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++)
     
103.     {
     
104.         Scalar color = colors[i%8];
     
105.         rectangle(img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)), cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height -1)*scale)), color, 3, 8, 0);
     
106. #if 0
     
107.         if (nestedCascade.empty()) {
     
108.           continue;
     
109.         }
     
110.         
     
111.         smallImgROI = smallImg(*r);
     
112.         nestedCascade.detectMultiScale(smallImgROI, nestedObjects, 1.1,2,0|CV_HAAR_SCALE_IMAGE, Size(30, 30));
     
113.          
     
114.         for (vector<Rect>::const_iterator nr=nestedObjects.begin(); nr != nestedObjects.end(); nr++)
     
115.         {
     
116.           center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
     
117.           center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
     
118.           radius = cvRound((nr->width + nr->height)*0.25*scale);
     
119.           circle(img, center, radius, color, 3,8,0);
     
120.         }
     
121. #endif
     
122.         
     
123.     }
     
124. 
     
125.     return faces.size();
     
126. }
     
127. 
     
128. 
     
129. gint delete_event(GtkWidget *widget, GdkEvent *event, gpointer data)
     
130. {
     
131.     return FALSE; //FALSE --> terminated application.
     
132. }
     
133. 
     
134. void destroy(GtkWidget *widget, gpointer data)
     
135. {
     
136.     gtk_main_quit();
     
137. }
     
138. 
     
139. static GtkWidget *window, *vbox, *drawingarea;
     
140. 
     
141. static gboolean on_draw_expose(GtkWidget *widget, GdkEventExpose *event, gpointer user_data)
     
142. {
     
143.   if (frame.total() == 640 * 480) {
     
144.     cvtColor(frame, frame, CV_BGR2RGB, 3);
     
145.     gdk_draw_rgb_image(widget->window, widget->style->fg_gc[GTK_STATE_NORMAL], 0, 0, 640, 480, GDK_RGB_DITHER_MAX, frame.data, 640*3);
     
146.   }
     
147.   return 1;
     
148. }
     
149. 
     
150. static void gtk_window_init(int argc, char **argv)
     
151. {
     
152.   gdk_threads_init();
     
153.   
     
154.   gtk_disable_setlocale();
     
155.   gtk_init(&argc, &argv);
     
156.   
     
157.   //windows
     
158.   window = gtk_window_new(GTK_WINDOW_TOPLEVEL);
     
159.   gtk_window_set_title(GTK_WINDOW(window), "USB Camera");
     
160.   gtk_window_set_position(GTK_WINDOW(window), GTK_WIN_POS_CENTER);
     
161.   gtk_window_set_default_size(GTK_WINDOW(window), 640,480);
     
162.   g_signal_connect(G_OBJECT(window), "delete_event", G_CALLBACK(delete_event), NULL);
     
163.   
     
164.   //vbox
     
165.   vbox = gtk_vbox_new(FALSE, 0);
     
166.   gtk_container_add(GTK_CONTAINER(window), vbox);
     
167.   
     
168.   //drawing area init
     
169.   drawingarea = gtk_drawing_area_new();
     
170.   gtk_box_pack_start(GTK_BOX(vbox), drawingarea, TRUE, TRUE, 0);
     
171.   gtk_drawing_area_size(GTK_DRAWING_AREA(drawingarea), 640,480);
     
172.   g_signal_connect(GTK_OBJECT(drawingarea), "expose-event", GTK_SIGNAL_FUNC(on_draw_expose), NULL);
     
173.   
     
174.   gtk_widget_show(vbox);
     
175.   gtk_widget_show(drawingarea);
     
176.   gtk_widget_show(window);
     
177. }
     
178. 
     
179. static void draw_thread(GtkWidget *widget)
     
180. {
     
181.   VideoCapture cap(0);
     
182.   if (!cap.isOpened()) {
     
183.     printf("camera open failed.\n");
     
184.     return;
     
185.   }
     
186.   
     
187.   for (;;) {
     
188.     g_usleep(10000);
     
189.     cap >> frame;
     
190.     detectAndDraw(frame, cascade, nestedCascade, scale);
     
191.     gdk_threads_enter();
     
192.     gtk_widget_queue_draw(GTK_WIDGET(widget)); //触发 expose event
     
193.     gdk_threads_leave();
     
194.   }
     
195. }
     
196. 
     
197. int main(int argc, char **argv)
     
198. {
     
199.   char l_dir[128];
     
200.   ydi_dirname(l_dir, sizeof(l_dir));
     
201.     
     
202.   string local_dir(l_dir) ;
     
203.   string cascadeName = local_dir + "/modules/haarcascade_frontalface_alt.xml";
     
204.   if( !cascade.load( cascadeName ) ) {
     
205.     cout << "ERROR: Could not load classifier cascade" << endl;
     
206.     return -1;
     
207.   }
     
208.   
     
209.   string nestedcascadeName = local_dir + "/modules/haarcascade_eye_tree_eyeglasses.xml";
     
210.   if( !nestedCascade.load( nestedcascadeName ) ) {
     
211.     cout << "ERROR: Could not load classifier nestedCascade" << endl;
     
212.     return -1;
     
213.   }
     
214. 
     
215.   gtk_window_init(argc, argv);
     
216.   
     
217.   GError* error = NULL;
     
218.   (void)g_thread_create((GThreadFunc)draw_thread, drawingarea, FALSE, &error);
     
219.   
     
220.   gdk_threads_enter();
     
221.   gtk_main();
     
222.   gdk_threads_leave();
     
223. 
     
224.   return 0;
     
225. }