質問編集履歴
7
プログラムのみやすさ改善
test
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test
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while (1){
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//カメラ情報のキャプチャー
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cap1 >> input_img1[j];
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cap2 >> input_img2[j];
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6
プログラムの問題点のみのとりあげ
test
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test
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```
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#include<pragma_lib.h>
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#include<cv.h>
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#include"opencv2/highgui/highgui.hpp"
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#include <cvaux.h>
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#include <omp.h>
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int main(int argc, char *argv[])
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{
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#pragma omp parallel
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IplImage *gray_img1 = 0, *gray_img2 = 0;
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CvCapture *capture1 = 0, *capture2 = 0;
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#pragma omp sections
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cap1.set(CV_CAP_PROP_FRAME_WIDTH, 640);
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cap1.set(CV_CAP_PROP_FRAME_HEIGHT, 480);
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VideoCapture cap2(1);
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cap2.set(CV_CAP_PROP_FRAME_WIDTH, 640);
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cap2.set(CV_CAP_PROP_FRAME_HEIGHT, 480);
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/* この設定は,利用するカメラに依存する */
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capture1 = cvCreateCameraCapture(0);
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capture2 = cvCreateCameraCapture(0);
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// (2)キャプチャサイズを設定する.
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cvSetCaptureProperty(capture1, CV_CAP_PROP_FRAME_WIDTH, 640);
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cvSetCaptureProperty(capture1, CV_CAP_PROP_FRAME_HEIGHT, 480);
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cvSetCaptureProperty(capture2, CV_CAP_PROP_FRAME_WIDTH, 640);
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cvSetCaptureProperty(capture2, CV_CAP_PROP_FRAME_HEIGHT, 480);
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96
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if (!cap1.isOpened())
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{
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#pragma omp section
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{
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while (1){
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p
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cap1 >> input_img1[j];
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102
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-
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cap2 >> input_img2[j];
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j++;
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if (j == 10){
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j = 0;
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}
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}
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}
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#pragma omp section
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{
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int k = 0;
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while (1){
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if (j != k){
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hsv_skin_img1 = Scalar(0, 0, 0);
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cvtColor(input_img1[k], hsv_img1, CV_BGR2HSV); //HSVに変換
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78
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79
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//問題の並列化したい作業
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81
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for (int y = 0; y < 480; y++)
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{
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for (int x = 0; x < 640; x++)
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{
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int a = hsv_img1.step*y + (x * 3);
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if (hsv_img1.data[a] >= 0 && hsv_img1.data[a] <= 15 && hsv_img1.data[a + 1] >= 50 && hsv_img1.data[a + 2] >= 50) //HSVでの検出
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{
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hsv_skin_img1.data[a] = 255; //肌色部分を青に
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}
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}
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}
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//IplImage *gray_img = cvCreateImage(cvGetSize(src_img), IPL_DEPTH_8U, 1);
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gray_img1 = cvCreateImage(cvGetSize(&(IplImage(hsv_skin_img1))), IPL_DEPTH_8U, 1);
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109
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// グレイスケールに変換
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cvCvtColor(&(IplImage(hsv_skin_img1)), gray_img1, CV_BGR2GRAY);
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CvMoments moments;
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117
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cvMoments(gray_img1, &moments, 0);
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119
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double m00 = cvGetSpatialMoment(&moments, 0, 0);
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121
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double m10 = cvGetSpatialMoment(&moments, 1, 0);
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123
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double m01 = cvGetSpatialMoment(&moments, 0, 1);
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int gX = m10 / m00, gY = m01 / m00;
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k = j;
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}
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}
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}
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136
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#pragma omp section
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138
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109
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{
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{
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int k = 0;
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while (1){
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if (j != k){
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hsv_skin_img2 = Scalar(0, 0, 0);
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cvtColor(input_img2[k], hsv_img2, CV_BGR2HSV); //HSVに変換
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// #pragma omp parallel forを使いたいが高速にならないため
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159
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//問題の並列化したい作業
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160
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161
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for (int y = 0; y < 480; y++)
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{
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for (int x = 0; x < 640; x++)
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{
|
168
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int a = hsv_img2.step*y + (x * 3);
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if (hsv_img2.data[a] >= 0 && hsv_img2.data[a] <= 15 && hsv_img2.data[a + 1] >= 50 && hsv_img2.data[a + 2] >= 50) //HSVでの検出
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173
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{
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175
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hsv_skin_img2.data[a] = 255; //肌色部分を青に
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}
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179
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}
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}
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//IplImage *gray_img = cvCreateImage(cvGetSize(src_img), IPL_DEPTH_8U, 1);
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186
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|
187
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gray_img2 = cvCreateImage(cvGetSize(&(IplImage(hsv_skin_img2))), IPL_DEPTH_8U, 1);
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188
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|
189
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+
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190
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191
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// グレイスケールに変換
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192
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|
193
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+
cvCvtColor(&(IplImage(hsv_skin_img2)), gray_img2, CV_BGR2GRAY);
|
194
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+
|
195
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+
CvMoments moments;
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196
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|
197
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+
cvMoments(gray_img2, &moments, 0);
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198
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|
199
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+
double m00 = cvGetSpatialMoment(&moments, 0, 0);
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200
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|
201
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+
double m10 = cvGetSpatialMoment(&moments, 1, 0);
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202
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|
203
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+
double m01 = cvGetSpatialMoment(&moments, 0, 1);
|
204
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|
205
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+
int gX = m10 / m00, gY = m01 / m00;
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206
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|
111
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printf("
|
207
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//printf("%d\n", j);
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112
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208
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|
209
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210
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113
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k = j;
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213
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}
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214
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215
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}
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216
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217
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}
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114
218
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115
219
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}
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116
220
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117
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Mat input_img1[10], input_img2[10];
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118
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|
119
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Mat hsv_skin_img1 = Mat(Size(640, 480), CV_8UC3);
|
120
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|
121
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Mat hsv_skin_img2 = Mat(Size(640, 480), CV_8UC3);
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122
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|
123
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Mat hsv_img1, hsv_img2;
|
124
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|
125
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126
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|
127
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int i = 0, n;
|
128
|
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|
129
|
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n = omp_get_max_threads(); // デフォルドのスレッド数を取得
|
130
|
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|
131
|
-
printf("max threads (default): %d\n", n);
|
132
|
-
|
133
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|
134
|
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|
135
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omp_set_num_threads(16); // スレッド数を変更
|
136
|
-
|
137
|
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n = omp_get_max_threads(); // スレッド数を再取得
|
138
|
-
|
139
|
-
printf("max threads (set): %d\n", n);
|
140
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|
141
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|
142
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|
143
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std::vector<int> v; // int 型動的配列
|
144
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|
145
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#pragma omp parallel
|
146
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|
147
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#pragma omp sections
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148
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|
149
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{
|
150
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151
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#pragma omp section
|
152
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|
153
|
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{
|
154
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155
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clock_t start = clock(); // スタート時間
|
156
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|
157
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|
158
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|
159
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while (1){
|
160
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|
161
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cap1 >> input_img1[j];
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162
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163
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cap2 >> input_img2[j];
|
164
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165
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j++;
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167
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if (j == 10){
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169
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j = 0;
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170
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171
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}
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172
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173
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}
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174
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|
175
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clock_t end = clock(); // 終了時間
|
176
|
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|
177
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std::cout << "duration = " << (double)(end - start) / CLOCKS_PER_SEC << "sec.\n";
|
178
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|
179
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}
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180
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|
181
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#pragma omp section
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182
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|
183
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{
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184
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185
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int k = 0;
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187
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while (1){
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189
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if (j != k){
|
190
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191
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|
192
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193
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hsv_skin_img1 = Scalar(0, 0, 0);
|
194
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|
195
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cvtColor(input_img1[k], hsv_img1, CV_BGR2HSV); //HSVに変換
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196
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|
197
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//問題の並列化したい作業
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198
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|
199
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for (int y = 0; y < 480; y++)
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200
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201
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{
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202
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203
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for (int x = 0; x < 640; x++)
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204
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|
205
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{
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206
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207
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int a = hsv_img1.step*y + (x * 3);
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208
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209
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if (hsv_img1.data[a] >= 0 && hsv_img1.data[a] <= 15 && hsv_img1.data[a + 1] >= 50 && hsv_img1.data[a + 2] >= 50) //HSVでの検出
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210
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|
211
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{
|
212
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|
213
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hsv_skin_img1.data[a] = 255; //肌色部分を青に
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214
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215
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}
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216
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217
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}
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218
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219
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}
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221
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222
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223
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//IplImage *gray_img = cvCreateImage(cvGetSize(src_img), IPL_DEPTH_8U, 1);
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224
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|
225
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gray_img1 = cvCreateImage(cvGetSize(&(IplImage(hsv_skin_img1))), IPL_DEPTH_8U, 1);
|
226
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|
227
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|
228
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|
229
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// グレイスケールに変換
|
230
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|
231
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cvCvtColor(&(IplImage(hsv_skin_img1)), gray_img1, CV_BGR2GRAY);
|
232
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|
233
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CvMoments moments;
|
234
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|
235
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cvMoments(gray_img1, &moments, 0);
|
236
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|
237
|
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double m00 = cvGetSpatialMoment(&moments, 0, 0);
|
238
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|
239
|
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double m10 = cvGetSpatialMoment(&moments, 1, 0);
|
240
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|
241
|
-
double m01 = cvGetSpatialMoment(&moments, 0, 1);
|
242
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|
243
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int gX = m10 / m00, gY = m01 / m00;
|
244
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245
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246
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247
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k = j;
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249
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}
|
250
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|
251
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}
|
252
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|
253
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-
}
|
254
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|
255
|
-
#pragma omp section
|
256
|
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|
257
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{
|
258
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|
259
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int k = 0;
|
260
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261
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while (1){
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262
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263
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if (j != k){
|
264
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265
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266
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267
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hsv_skin_img2 = Scalar(0, 0, 0);
|
268
|
-
|
269
|
-
|
270
|
-
|
271
|
-
cvtColor(input_img2[k], hsv_img2, CV_BGR2HSV); //HSVに変換
|
272
|
-
|
273
|
-
|
274
|
-
|
275
|
-
// #pragma omp parallel forを使いたいが高速にならないため
|
276
|
-
|
277
|
-
//問題の並列化したい作業
|
278
|
-
|
279
|
-
for (int y = 0; y < 480; y++)
|
280
|
-
|
281
|
-
{
|
282
|
-
|
283
|
-
for (int x = 0; x < 640; x++)
|
284
|
-
|
285
|
-
{
|
286
|
-
|
287
|
-
int a = hsv_img2.step*y + (x * 3);
|
288
|
-
|
289
|
-
if (hsv_img2.data[a] >= 0 && hsv_img2.data[a] <= 15 && hsv_img2.data[a + 1] >= 50 && hsv_img2.data[a + 2] >= 50) //HSVでの検出
|
290
|
-
|
291
|
-
{
|
292
|
-
|
293
|
-
hsv_skin_img2.data[a] = 255; //肌色部分を青に
|
294
|
-
|
295
|
-
}
|
296
|
-
|
297
|
-
}
|
298
|
-
|
299
|
-
}
|
300
|
-
|
301
|
-
|
302
|
-
|
303
|
-
//IplImage *gray_img = cvCreateImage(cvGetSize(src_img), IPL_DEPTH_8U, 1);
|
304
|
-
|
305
|
-
gray_img2 = cvCreateImage(cvGetSize(&(IplImage(hsv_skin_img2))), IPL_DEPTH_8U, 1);
|
306
|
-
|
307
|
-
|
308
|
-
|
309
|
-
// グレイスケールに変換
|
310
|
-
|
311
|
-
cvCvtColor(&(IplImage(hsv_skin_img2)), gray_img2, CV_BGR2GRAY);
|
312
|
-
|
313
|
-
CvMoments moments;
|
314
|
-
|
315
|
-
cvMoments(gray_img2, &moments, 0);
|
316
|
-
|
317
|
-
double m00 = cvGetSpatialMoment(&moments, 0, 0);
|
318
|
-
|
319
|
-
double m10 = cvGetSpatialMoment(&moments, 1, 0);
|
320
|
-
|
321
|
-
double m01 = cvGetSpatialMoment(&moments, 0, 1);
|
322
|
-
|
323
|
-
int gX = m10 / m00, gY = m01 / m00;
|
324
|
-
|
325
|
-
//printf("%d\n", j);
|
326
|
-
|
327
|
-
|
328
|
-
|
329
|
-
k = j;
|
330
|
-
|
331
|
-
}
|
332
|
-
|
333
|
-
}
|
334
|
-
|
335
|
-
}
|
336
|
-
|
337
|
-
}
|
338
|
-
|
339
221
|
getchar();
|
340
222
|
|
341
223
|
}
|
5
文章の改善
test
CHANGED
File without changes
|
test
CHANGED
@@ -14,11 +14,13 @@
|
|
14
14
|
|
15
15
|
カメラからの情報取得と左右それぞれのカメラ結果の画像処理まで
|
16
16
|
|
17
|
+
並列化ができており、
|
18
|
+
|
17
|
-
|
19
|
+
そこから画像処理したものの色の抽出を行う段階での
|
18
|
-
|
20
|
+
|
19
|
-
並列化がうまくいかずおそらく順次処理の動きになっています
|
21
|
+
並列化がうまくいかず、おそらく順次処理の動きになってしまいます
|
20
|
-
|
22
|
+
|
21
|
-
OpenMPでは並列
|
23
|
+
OpenMPでは並列にさらに並列を重ねることはできないのでしょうか
|
22
24
|
|
23
25
|
またできない場合には別の方法があれば教えてください
|
24
26
|
|
4
見易さ改善
test
CHANGED
File without changes
|
test
CHANGED
@@ -24,6 +24,10 @@
|
|
24
24
|
|
25
25
|
|
26
26
|
|
27
|
+
*実際のプログラムではうまくいかなかった色抽出の並列化や球の距離計測部分は省略しております
|
28
|
+
|
29
|
+
|
30
|
+
|
27
31
|
```
|
28
32
|
|
29
33
|
#include<pragma_lib.h>
|
3
インテントの追加
test
CHANGED
File without changes
|
test
CHANGED
@@ -98,7 +98,7 @@
|
|
98
98
|
|
99
99
|
}
|
100
100
|
|
101
|
-
if (!cap2.isOpened())
|
101
|
+
if (!cap2.isOpened())
|
102
102
|
|
103
103
|
{
|
104
104
|
|
2
動きの改善
test
CHANGED
File without changes
|
test
CHANGED
@@ -98,6 +98,16 @@
|
|
98
98
|
|
99
99
|
}
|
100
100
|
|
101
|
+
if (!cap2.isOpened())
|
102
|
+
|
103
|
+
{
|
104
|
+
|
105
|
+
printf("カメラが検出できませんでした");
|
106
|
+
|
107
|
+
return -1;
|
108
|
+
|
109
|
+
}
|
110
|
+
|
101
111
|
Mat input_img1[10], input_img2[10];
|
102
112
|
|
103
113
|
Mat hsv_skin_img1 = Mat(Size(640, 480), CV_8UC3);
|
1
みやすく
test
CHANGED
File without changes
|
test
CHANGED
@@ -140,7 +140,7 @@
|
|
140
140
|
|
141
141
|
|
142
142
|
|
143
|
-
while (
|
143
|
+
while (1){
|
144
144
|
|
145
145
|
cap1 >> input_img1[j];
|
146
146
|
|
@@ -168,7 +168,7 @@
|
|
168
168
|
|
169
169
|
int k = 0;
|
170
170
|
|
171
|
-
while (
|
171
|
+
while (1){
|
172
172
|
|
173
173
|
if (j != k){
|
174
174
|
|
@@ -242,7 +242,7 @@
|
|
242
242
|
|
243
243
|
int k = 0;
|
244
244
|
|
245
|
-
while (
|
245
|
+
while (1){
|
246
246
|
|
247
247
|
if (j != k){
|
248
248
|
|