推 ilove88th: 你的 kernel 後面冒出的 int i 跟 j 怎麼來的？ 11/14 22:08
→ ilove88th: 跟 x 還有 y 完全沒關係啊 …. 11/14 22:08
推 GTX9487: 正確做法是從 host copy 到 device 11/14 23:48
→ GTX9487: 再從 device 丟回來 host 再 print 11/14 23:48
開發平台(Platform): (Ex: Win10, Linux, ...)
Win10
編譯器(Ex: GCC, clang, VC++...)+目標環境(跟開發平台不同的話需列出)
VC++
額外使用到的函數庫(Library Used): (Ex: OpenGL, ...)
opencv
Cuda
問題(Question)：
我想將opencv的cuda數據處理完後
在自己寫核函數去處理
結果發現10*10的數據
只有一行有 其他都是0
想問一下為什麼會這樣
我哪裡寫錯了
謝謝
餵入的資料(Input)：
[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
預期的正確結果(Expected Output)：
[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9;
0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
錯誤結果(Wrong Output)：
0 ,1 ,2 ,3 ,4 ,5 ,6 ,7 ,8 ,9 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,
程式碼(Code)：(請善用置底文網頁, 記得排版，禁止使用圖檔)
__global__ void test1_Kernel(char* src_image,int length)
{
int y = blockIdx.y * blockDim.y + threadIdx.y;
int x = blockIdx.x * blockDim.x + threadIdx.x;
int index = 10 * y + x;
if (index != 0)
{
return;
}
for (int i = 0; i < 10; i++)
{
printf("\n");
for (int j = 0; j < 10; j++)
{
printf("%d ,", (int)src_image[i*10+j]);
}
}
}
void test1_withCuda()
{
cv::Mat src_image = Mat::zeros(Size(10,10), CV_8UC1);
for (int i = 0; i < 10; i++)
{
for (int j = 0; j < 10; j++)
{
src_image.data[i * 10 + j]=j;
}
}
//capture >> src_image;
cv::Mat dst_image;
cv::cuda::GpuMat d_src_img;
cv::cuda::GpuMat d_dst_img;
cout << src_image << endl;
d_src_img.upload(src_image);
int size_temp = d_src_img.rows * d_src_img.cols;
cout << size_temp << endl;
test1_Kernel << <10, 10 >> > ((char*)d_src_img.data, size_temp);
cudaDeviceSynchronize();
waitKey(0);
}
放
補充說明(Supplement)：
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