opencv 人工智能计算机视觉 RK3588 RGA 图像操作

背景

公司业务需要用到RK3588 的RGA进行图像处理加速，网上搜了下，这方面的资料很少，在此记录下自己从熟悉文档到应用的整个过程，给有相关需求的小伙伴做个参考。

一、什么是RGA

RGA (Raster Graphic Acceleration Unit)是一个独立的2D硬件加速器，可用于加速点/线绘制，执行图像缩放、旋转、格式转换等常见的2D图形操作。

二、RK3588 RGA及代码示例

2.1 从git拉取官方文档及sample示例

git clone https://github.com/airockchip/librga

cd librga

其中 include 是相关头文件，libs是运行库，samples是代码示例。注意：官方demo是有默认的验证源文件，开始前先看下图对应的md文件。

2.2 图像缩放或者放大

本示例代码是在官方resize_demo的基础上进行改动、验证。说明：因为是Debian系统，安装opencv会报错，缺少libjasper库。网上搜了下比较麻烦，本人使用的先在Ubuntu先编译好的opencv库。

代码功能：使用opencv读取本地 1.jpg 图片，调用RGA resize接口进行图片缩小和放大，再使用opencv保存为新的文件。BIG宏定义是用来执行控制放大还缩操作。

#include

#include "im2d_version.h"

#include "im2d_type.h"

#include "im2d_single.h"

#include "im2d_common.h"

#include "im2d_buffer.h"

#include "RgaUtils.h"

#include "src/utils/utils.h"

#include "./opencv2/core/core.hpp"

#include "./opencv2/highgui/highgui.hpp"

using namespace std;

using namespace cv;

#define BIG

#ifdef BIG

#define RESIZE_WIDTH 1920

#define RESIZE_HEIGHT 1080

#define SCALE_NAME "./scale_1920_1080.jpg"

#else

#define RESIZE_WIDTH 640

#define RESIZE_HEIGHT 480

#define SCALE_NAME "./zoom_640_480.jpg"

#endif

int main(int argc, char **argv)

{

clock_t t1, t2;

t1 = clock();

int ret = 0;

int src_width, src_height, src_format;

int dst_width, dst_height, dst_format;

char *src_buf, *dst_buf;

int src_buf_size, dst_buf_size;

rga_buffer_t src_img, dst_img;

rga_buffer_handle_t src_handle, dst_handle;

memset(&src_img, 0, sizeof(src_img));

memset(&dst_img, 0, sizeof(dst_img));

Mat image, res;

image = imread("./1.jpg");

if (image.data == nullptr)

{

cout << "图片文件不存在" << endl;

}

cout << "图像宽为：" << image.cols << "\t高度为：" << image.rows << "\t通道数为：" << image.channels() << endl;

src_width = image.cols;

src_height = image.rows;

src_format = RK_FORMAT_BGR_888;

// src_format = RK_FORMAT_RGBA_8888; // RK_FORMAT_YCbCr_420_SP

dst_width = RESIZE_WIDTH;

dst_height = RESIZE_HEIGHT;

dst_format = RK_FORMAT_BGR_888;

src_buf_size = src_width * src_height * get_bpp_from_format(src_format);

dst_buf_size = dst_width * dst_height * get_bpp_from_format(dst_format);

cout << " src format: " << get_bpp_from_format(src_format) << endl;

cout << " dst format: " << get_bpp_from_format(dst_format) << endl;

src_buf = (char *)malloc(src_buf_size);

dst_buf = (char *)malloc(dst_buf_size);

memcpy(src_buf, image.data, src_width * src_height * get_bpp_from_format(src_format));

memset(dst_buf, 0x80, dst_buf_size);

src_handle = importbuffer_virtualaddr(src_buf, src_buf_size);

dst_handle = importbuffer_virtualaddr(dst_buf, dst_buf_size);

if (src_handle == 0 || dst_handle == 0) {

printf("importbuffer failed!\n");

// goto release_buffer;

return -1;

}

src_img = wrapbuffer_handle(src_handle, src_width, src_height, src_format);

dst_img = wrapbuffer_handle(dst_handle, dst_width, dst_height, dst_format);

ret = imcheck(src_img, dst_img, {}, {});

if (IM_STATUS_NOERROR != ret) {

printf("%d, check error! %s", __LINE__, imStrError((IM_STATUS)ret));

return -1;

}

printf("%d, check success \n", __LINE__);

ret = imresize(src_img, dst_img);

if (ret == IM_STATUS_SUCCESS) {

printf("imresize running success!\n");

} else {

printf("running failed, %s\n", imStrError((IM_STATUS)ret));

// goto release_buffer;

return -1;

}

t2 = clock();

double time_use = (double)(t2 - t1) / CLOCKS_PER_SEC; // 微秒

printf("vptdt_init time_use is [%f] s\n", time_use);

res.create(RESIZE_HEIGHT, RESIZE_WIDTH, CV_8UC3);

memcpy(res.data, dst_buf, RESIZE_HEIGHT*RESIZE_WIDTH*3);

cv::imwrite(SCALE_NAME, res);

printf("save picture: [ %s ] success\n", SCALE_NAME);

release_buffer:

if (src_handle)

releasebuffer_handle(src_handle);

if (dst_handle)

releasebuffer_handle(dst_handle);

if (src_buf)

free(src_buf);

if (dst_buf)

free(dst_buf);

return ret;

return 0;

}

2.2 图像格式转换

本示例代码是在官方cvtcolor_demo的基础上进行改动、验证。代码功能：

打开宏定义BGR2NV12 ，使用opencv读取本地1.jpg图片，调用RGA imcvtcolor 接口实现BGR到YUV的转换；关闭宏定义BGR2NV12，读取YUV文件，调用RGA imcvtcolor 接口实现YUV到BGR的转换；

#include

#include "im2d_version.h"

#include "im2d_type.h"

#include "im2d_single.h"

#include "im2d_common.h"

#include "im2d_buffer.h"

#include "RgaUtils.h"

#include "src/utils/utils.h"

#include "./opencv2/core/core.hpp"

#include "./opencv2/highgui/highgui.hpp"

#include "./opencv4/opencv2/opencv.hpp"

using namespace std;

using namespace cv;

#define TRANSFER_FILE "./transfer.YUV"

#define RGA_WRITE_FILE "./rga_res.jpg"

#define OPENCV_WRITE_FILE "./opecv_res.jpg"

#define BGR2NV12

// #define OPENCV_TRANSFER

int main(int argc, char **argv)

{

int ret = 0;

int src_width, src_height, src_format;

int dst_width, dst_height, dst_format;

char *src_buf, *dst_buf;

int src_buf_size, dst_buf_size;

rga_buffer_t src_img, dst_img;

rga_buffer_handle_t src_handle, dst_handle;

memset(&src_img, 0, sizeof(src_img));

memset(&dst_img, 0, sizeof(dst_img));

#ifdef BGR2NV12

clock_t t1, t2;

t1 = clock();

Mat image, res;

image = imread("./1.jpg");

if (image.data == nullptr)

{

cout << "图片文件不存在" << endl;

}

cout << "图像宽为：" << image.cols << "\t高度为：" << image.rows << "\t通道数为：" << image.channels() << endl;

src_width = image.cols;

src_height = image.rows;

src_format = RK_FORMAT_BGR_888;

dst_width = image.cols;

dst_height = image.rows;

dst_format = RK_FORMAT_YCbCr_420_SP; // NV12

cout << " src format: " << get_bpp_from_format(src_format) << endl;

cout << " dst format: " << get_bpp_from_format(dst_format) << endl;

src_buf_size = src_width * src_height * get_bpp_from_format(src_format);

dst_buf_size = dst_width * dst_height * get_bpp_from_format(dst_format);

src_buf = (char *)malloc(src_buf_size);

dst_buf = (char *)malloc(dst_buf_size);

memcpy(src_buf, image.data, src_width * src_height * get_bpp_from_format(src_format));

memset(dst_buf, 0x80, dst_buf_size);

src_handle = importbuffer_virtualaddr(src_buf, src_buf_size);

dst_handle = importbuffer_virtualaddr(dst_buf, dst_buf_size);

if (src_handle == 0 || dst_handle == 0)

{

printf("importbuffer failed!\n");

if (src_handle)

releasebuffer_handle(src_handle);

if (dst_handle)

releasebuffer_handle(dst_handle);

if (src_buf)

free(src_buf);

if (dst_buf)

free(dst_buf);

return ret;

}

src_img = wrapbuffer_handle(src_handle, src_width, src_height, src_format);

dst_img = wrapbuffer_handle(dst_handle, dst_width, dst_height, dst_format);

ret = imcheck(src_img, dst_img, {}, {});

if (IM_STATUS_NOERROR != ret)

{

printf("%d, check error! %s", __LINE__, imStrError((IM_STATUS)ret));

return -1;

}

// ret = imcvtcolor(src_img, dst_img, src_format, dst_format, IM_RGB_TO_YUV_BT709_LIMIT);

ret = imcvtcolor(src_img, dst_img, src_format, dst_format, IM_RGB_TO_YUV_BT709_LIMIT);

if (ret == IM_STATUS_SUCCESS)

{

printf("imcvtcolor running success!\n");

}

else

{

printf("imcvtcolo rrunning failed, %s\n", imStrError((IM_STATUS)ret));

if (src_handle)

releasebuffer_handle(src_handle);

if (dst_handle)

releasebuffer_handle(dst_handle);

if (src_buf)

free(src_buf);

if (dst_buf)

free(dst_buf);

return ret;

}

t2 = clock();

double time_use = (double)(t2 - t1) / CLOCKS_PER_SEC; // 微秒

printf("imcvtcolo to YUV time_use is [%f] s\n", time_use);

FILE *file = fopen(TRANSFER_FILE, "wb+");

if (!file)

{

fprintf(stderr, "Could not open %s\n", TRANSFER_FILE);

return false;

}

else

{

fprintf(stderr, "open %s and write ok\n", TRANSFER_FILE);

}

fwrite(dst_buf, image.cols * image.rows * get_bpp_from_format(dst_format), 1, file);

fclose(file);

#else

src_width = 1920;

src_height = 1080;

src_format = RK_FORMAT_YCbCr_420_SP; // NV12

#ifdef OPENCV_TRANSFER

cout << " src format: " << get_bpp_from_format(src_format) << endl;

src_buf_size = src_width * src_height * get_bpp_from_format(src_format);

src_buf = (char *)malloc(src_buf_size);

FILE *file = fopen(TRANSFER_FILE, "rb");

if (!file)

{

fprintf(stderr, "Could not open %s\n", TRANSFER_FILE);

return -EINVAL;

}

fread(src_buf, src_width * src_height * get_bpp_from_format(src_format), 1, file);

fclose(file);

cv::Mat yuvNV12, rgb24;

yuvNV12.create(src_height * 3 / 2, src_width, CV_8UC1);

memcpy(yuvNV12.data, src_buf, src_width*src_height * 3 / 2);

// trans to rgb24

cv::cvtColor(yuvNV12, rgb24, cv::COLOR_YUV2BGR_NV12);

cv::imwrite(OPENCV_WRITE_FILE, rgb24);

printf("[OPENCV] save picture: [ %s ] success\n", OPENCV_WRITE_FILE);

free(src_buf);

src_buf = NULL;

#else

clock_t t1, t2;

t1 = clock();

dst_width = 1920;

dst_height = 1080;

dst_format = RK_FORMAT_BGR_888;

cout << "src format: " << get_bpp_from_format(src_format) << endl;

cout << "dst format: " << get_bpp_from_format(dst_format) << endl;

src_buf_size = src_width * src_height * get_bpp_from_format(src_format);

dst_buf_size = dst_width * dst_height * get_bpp_from_format(dst_format);

src_buf = (char *)malloc(src_buf_size);

dst_buf = (char *)malloc(dst_buf_size);

FILE *file = fopen(TRANSFER_FILE, "rb");

if (!file)

{

fprintf(stderr, "Could not open %s\n", TRANSFER_FILE);

return -EINVAL;

}

fread(src_buf, src_width * src_height * get_bpp_from_format(src_format), 1, file);

fclose(file);

printf("read src file success!\n");

memset(dst_buf, 0x80, dst_buf_size);

src_handle = importbuffer_virtualaddr(src_buf, src_buf_size);

dst_handle = importbuffer_virtualaddr(dst_buf, dst_buf_size);

if (src_handle == 0 || dst_handle == 0)

{

printf("importbuffer failed!\n");

if (src_handle)

releasebuffer_handle(src_handle);

if (dst_handle)

releasebuffer_handle(dst_handle);

if (src_buf)

free(src_buf);

if (dst_buf)

free(dst_buf);

return ret;

}

src_img = wrapbuffer_handle(src_handle, src_width, src_height, src_format);

dst_img = wrapbuffer_handle(dst_handle, dst_width, dst_height, dst_format);

ret = imcheck(src_img, dst_img, {}, {});

if (IM_STATUS_NOERROR != ret)

{

printf("%d, check error! %s", __LINE__, imStrError((IM_STATUS)ret));

return -1;

}

ret = imcvtcolor(src_img, dst_img, src_format, dst_format, IM_YUV_TO_RGB_BT709_LIMIT);

if (ret == IM_STATUS_SUCCESS)

{

printf("imcvtcolor running success!\n");

}

else

{

printf("imcvtcolo rrunning failed, %s\n", imStrError((IM_STATUS)ret));

if (src_handle)

releasebuffer_handle(src_handle);

if (dst_handle)

releasebuffer_handle(dst_handle);

if (src_buf)

free(src_buf);

if (dst_buf)

free(dst_buf);

return ret;

}

t2 = clock();

double time_use = (double)(t2 - t1) / CLOCKS_PER_SEC; // 微秒

printf("imcvtcolo YUV to BGR time_use is [%f] s\n", time_use);

Mat rgb24;

rgb24.create(src_height, src_width, CV_8UC3);

memcpy(rgb24.data, dst_buf, dst_width*dst_height*3);

cv::imwrite(RGA_WRITE_FILE, rgb24);

printf("[RGA] save picture: [ %s ] success\n", RGA_WRITE_FILE);

#endif // OPENCV_TRANSFER

#endif

return 0;

}

推荐链接

评论可见，请评论后查看内容，谢谢！！！

您阅读本篇文章共花了：

金钥匙

opencv 人工智能计算机视觉 RK3588 RGA 图像操作

运维数据库 R730服务器热插拔换磁盘（raid阵列）

神经网络计算机视觉深度学习 CNN经典网络模型（五）：ResNet简介及代码实现（PyTorch超详细注释版）

发表评论取消回复

金钥匙

opencv 人工智能 计算机视觉 RK3588 RGA 图像操作

运维 数据库 R730服务器热插拔换磁盘（raid阵列）

神经网络 计算机视觉 深度学习 CNN经典网络模型（五）：ResNet简介及代码实现（PyTorch超详细注释版）

相关文章

发表评论取消回复

opencv 人工智能计算机视觉 RK3588 RGA 图像操作

运维数据库 R730服务器热插拔换磁盘（raid阵列）

神经网络计算机视觉深度学习 CNN经典网络模型（五）：ResNet简介及代码实现（PyTorch超详细注释版）