From 8b06b1cbf112d55307ea8a6efe711db4e7506d89 Mon Sep 17 00:00:00 2001
From: admin <weikou2014>
Date: 星期二, 07 三月 2023 10:13:47 +0800
Subject: [PATCH] 'GPU内核方法优化'
---
ConsoleApplication/OpenCLExcuter.cpp | 82 +++++++++++++++++++++++++++++++++++++++++
1 files changed, 82 insertions(+), 0 deletions(-)
diff --git a/ConsoleApplication/OpenCLExcuter.cpp b/ConsoleApplication/OpenCLExcuter.cpp
index b16ac4c..be2924b 100644
--- a/ConsoleApplication/OpenCLExcuter.cpp
+++ b/ConsoleApplication/OpenCLExcuter.cpp
@@ -1098,6 +1098,88 @@
}
+void OpenCLExcuter::splitRowData(cv::Mat img, int* rowIndexs, int lines, int ele_count_per_line, int* result)
+{
+
+
+ kernel = clCreateKernel(program, "splitRowData", &error);
+ if (kernel == NULL) {
+ throw string("Couldn't create kernel!\n");
+ }
+
+
+ int inputSize = img.cols * img.rows;
+ int resultSize = lines * ele_count_per_line * 4;
+
+
+ //创建缓存对象
+
+ cl_mem memObject1 = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(uchar) * inputSize, img.data, &error);
+ if (error < 0) {
+ throw string("Creat memObject1 failed!\n");
+ }
+
+ cl_mem memObject2 = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(int) * lines * 4, rowIndexs, &error);
+ if (error < 0) {
+ throw string("Creat memObject2 failed!\n");
+ }
+
+
+ cl_mem memObject3 = clCreateBuffer(context, CL_MEM_WRITE_ONLY,
+ sizeof(int) * resultSize, NULL, &error);
+ if (error < 0) {
+ throw string("Creat memObject3 failed!\n");
+ }
+
+ try {
+ //设置内核参数
+ int min_empty_width = 5;
+ int threshhold_color = _IMG_BINARY_THRESHOLD;
+ error = clSetKernelArg(kernel, 0, sizeof(cl_mem), &memObject1);
+ error = clSetKernelArg(kernel, 1, sizeof(cl_mem), &memObject2);
+ error |= clSetKernelArg(kernel, 2, sizeof(int), &img.cols);
+ error |= clSetKernelArg(kernel, 3, sizeof(int), &ele_count_per_line);
+ error |= clSetKernelArg(kernel, 4, sizeof(int), &min_empty_width);
+ error |= clSetKernelArg(kernel, 5, sizeof(int), &threshhold_color);
+ error |= clSetKernelArg(kernel, 6, sizeof(cl_mem), &memObject3);
+
+ if (error != CL_SUCCESS) {
+ throw string("Error setting kernel arguments!\n");
+ }
+ //执行内核
+ size_t globalWorkSize[1] = { lines };
+ size_t localWorkSize[1] = { 1 };
+
+ const int work_dim = 1;
+
+ error = clEnqueueNDRangeKernel(queue, kernel, work_dim, NULL, globalWorkSize,
+ localWorkSize, 0, NULL, NULL);
+ if (error != CL_SUCCESS) {
+ throw string("Error queuing kernel for execution!\n");
+ }
+
+ //读取执行结果
+ error = clEnqueueReadBuffer(queue, memObject3, CL_TRUE, 0, resultSize * sizeof(int),
+ result, 0, NULL, NULL);
+ if (error != CL_SUCCESS) {
+ throw string("Error reading result buffer!\n");
+ }
+ clReleaseKernel(kernel);
+ clReleaseMemObject(memObject1);
+ clReleaseMemObject(memObject2);
+ clReleaseMemObject(memObject3);
+ }
+ catch (string st) {
+ clReleaseKernel(kernel);
+ clReleaseMemObject(memObject1);
+ clReleaseMemObject(memObject2);
+ clReleaseMemObject(memObject3);
+ excuteError();
+ throw st;
+ }
+
+}
+
void OpenCLExcuter::splitPlateContentRowData(unsigned char* imgs, int imgWidth, int imgHeight, int* rowIndexs, int lines, int lineEleCount, int fromIndex, int toIndex,
--
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