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Open Source Computer Vision Library
https://opencv.org/
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214 lines
6.4 KiB
214 lines
6.4 KiB
#include <iostream> |
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#include <stdexcept> |
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//wrappers |
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#include "ivx.hpp" |
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//OpenCV includes |
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#include "opencv2/core.hpp" |
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#include "opencv2/imgproc.hpp" |
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#include "opencv2/imgcodecs.hpp" |
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#include "opencv2/highgui.hpp" |
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enum UserMemoryMode |
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{ |
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COPY, USER_MEM, MAP |
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}; |
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ivx::Graph createProcessingGraph(ivx::Image& inputImage, ivx::Image& outputImage); |
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int ovxDemo(std::string inputPath, UserMemoryMode mode); |
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ivx::Graph createProcessingGraph(ivx::Image& inputImage, ivx::Image& outputImage) |
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{ |
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using namespace ivx; |
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Context context = inputImage.get<Context>(); |
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Graph graph = Graph::create(context); |
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vx_uint32 width = inputImage.width(); |
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vx_uint32 height = inputImage.height(); |
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// Intermediate images |
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Image |
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smoothed = Image::createVirtual(graph), |
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cannied = Image::createVirtual(graph), |
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halfImg = Image::create(context, width, height, VX_DF_IMAGE_U8), |
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halfCanny = Image::create(context, width, height, VX_DF_IMAGE_U8); |
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// Constants |
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vx_uint32 threshCannyMin = 127; |
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vx_uint32 threshCannyMax = 192; |
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Threshold threshCanny = Threshold::createRange(context, VX_TYPE_UINT8, threshCannyMin, threshCannyMax); |
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ivx::Scalar alpha = ivx::Scalar::create<VX_TYPE_FLOAT32>(context, 0.5); |
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// Sequence of some image operations |
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// Node can also be added in function-like style |
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nodes::gaussian3x3(graph, inputImage, smoothed); |
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Node::create(graph, VX_KERNEL_CANNY_EDGE_DETECTOR, smoothed, threshCanny, |
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ivx::Scalar::create<VX_TYPE_INT32>(context, 3), |
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ivx::Scalar::create<VX_TYPE_ENUM>(context, VX_NORM_L2), cannied); |
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Node::create(graph, VX_KERNEL_ACCUMULATE_WEIGHTED, inputImage, alpha, halfImg); |
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Node::create(graph, VX_KERNEL_ACCUMULATE_WEIGHTED, cannied, alpha, halfCanny); |
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Node::create(graph, VX_KERNEL_ADD, halfImg, halfCanny, |
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ivx::Scalar::create<VX_TYPE_ENUM>(context, VX_CONVERT_POLICY_SATURATE), outputImage); |
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graph.verify(); |
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return graph; |
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} |
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int ovxDemo(std::string inputPath, UserMemoryMode mode) |
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{ |
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using namespace cv; |
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using namespace ivx; |
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Mat image = imread(inputPath, IMREAD_GRAYSCALE); |
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if (image.empty()) return -1; |
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//check image format |
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if (image.depth() != CV_8U || image.channels() != 1) return -1; |
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try |
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{ |
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Context context = Context::create(); |
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//put user data from cv::Mat to vx_image |
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vx_df_image color = Image::matTypeToFormat(image.type()); |
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vx_uint32 width = image.cols, height = image.rows; |
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Image ivxImage; |
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if (mode == COPY) |
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{ |
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ivxImage = Image::create(context, width, height, color); |
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ivxImage.copyFrom(0, image); |
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} |
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else |
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{ |
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ivxImage = Image::createFromHandle(context, color, Image::createAddressing(image), image.data); |
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} |
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Image ivxResult; |
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Image::Patch resultPatch; |
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Mat output; |
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if (mode == COPY || mode == MAP) |
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{ |
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//we will copy or map data from vx_image to cv::Mat |
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ivxResult = ivx::Image::create(context, width, height, VX_DF_IMAGE_U8); |
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} |
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else // if (mode == MAP_TO_VX) |
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{ |
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//create vx_image based on user data, no copying required |
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output = cv::Mat(height, width, CV_8U, cv::Scalar(0)); |
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ivxResult = Image::createFromHandle(context, Image::matTypeToFormat(CV_8U), |
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Image::createAddressing(output), output.data); |
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} |
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Graph graph = createProcessingGraph(ivxImage, ivxResult); |
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// Graph execution |
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graph.process(); |
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//getting resulting image in cv::Mat |
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if (mode == COPY) |
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{ |
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ivxResult.copyTo(0, output); |
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} |
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else if (mode == MAP) |
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{ |
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//create cv::Mat based on vx_image mapped data |
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resultPatch.map(ivxResult, 0, ivxResult.getValidRegion()); |
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//generally this is very bad idea! |
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//but in our case unmap() won't happen until output is in use |
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output = resultPatch.getMat(); |
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} |
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else // if (mode == MAP_TO_VX) |
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{ |
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#ifdef VX_VERSION_1_1 |
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//we should take user memory back from vx_image before using it (even before reading) |
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ivxResult.swapHandle(); |
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#endif |
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} |
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//here output goes |
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cv::imshow("processing result", output); |
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cv::waitKey(0); |
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cv::destroyAllWindows(); |
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#ifdef VX_VERSION_1_1 |
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if (mode != COPY) |
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{ |
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//we should take user memory back before release |
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//(it's not done automatically according to standard) |
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ivxImage.swapHandle(); |
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if (mode == USER_MEM) ivxResult.swapHandle(); |
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} |
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#endif |
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//the line is unnecessary since unmapping is done on destruction of patch |
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//resultPatch.unmap(); |
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} |
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catch (const ivx::RuntimeError& e) |
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{ |
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std::cerr << "Error: code = " << e.status() << ", message = " << e.what() << std::endl; |
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return e.status(); |
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} |
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catch (const ivx::WrapperError& e) |
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{ |
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std::cerr << "Error: message = " << e.what() << std::endl; |
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return -1; |
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} |
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return 0; |
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} |
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int main(int argc, char *argv[]) |
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{ |
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const std::string keys = |
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"{help h usage ? | | }" |
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"{image | <none> | image to be processed}" |
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"{mode | copy | user memory interaction mode: \n" |
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"copy: create VX images and copy data to/from them\n" |
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"user_mem: use handles to user-allocated memory\n" |
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"map: map resulting VX image to user memory}" |
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; |
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cv::CommandLineParser parser(argc, argv, keys); |
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parser.about("OpenVX interoperability sample demonstrating OpenVX wrappers usage." |
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"The application loads an image, processes it with OpenVX graph and outputs result in a window"); |
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if (parser.has("help")) |
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{ |
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parser.printMessage(); |
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return 0; |
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} |
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std::string imgPath = parser.get<std::string>("image"); |
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std::string modeString = parser.get<std::string>("mode"); |
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UserMemoryMode mode; |
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if(modeString == "copy") |
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{ |
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mode = COPY; |
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} |
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else if(modeString == "user_mem") |
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{ |
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mode = USER_MEM; |
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} |
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else if(modeString == "map") |
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{ |
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mode = MAP; |
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} |
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else |
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{ |
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std::cerr << modeString << ": unknown memory mode" << std::endl; |
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return -1; |
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} |
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if (!parser.check()) |
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{ |
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parser.printErrors(); |
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return -1; |
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} |
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return ovxDemo(imgPath, mode); |
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}
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