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7ed557497d
[GAPI] Support basic inference in OAK backend * Combined commit which enables basic inference and other extra capabilities of OAK backend * Remove unnecessary target options from the cmakelist
123 lines
4.1 KiB
C++
123 lines
4.1 KiB
C++
#include <algorithm>
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#include <iostream>
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#include <sstream>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/imgcodecs.hpp>
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#include <opencv2/gapi.hpp>
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#include <opencv2/gapi/core.hpp>
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#include <opencv2/gapi/imgproc.hpp>
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#include <opencv2/gapi/infer.hpp>
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#include <opencv2/gapi/infer/parsers.hpp>
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#include <opencv2/gapi/render.hpp>
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#include <opencv2/gapi/cpu/gcpukernel.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/gapi/oak/oak.hpp>
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#include <opencv2/gapi/oak/infer.hpp>
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const std::string keys =
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"{ h help | | Print this help message }"
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"{ detector | | Path to compiled .blob face detector model }"
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"{ duration | 100 | Number of frames to pull from camera and run inference on }";
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namespace custom {
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G_API_NET(FaceDetector, <cv::GMat(cv::GFrame)>, "sample.custom.face-detector");
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using GDetections = cv::GArray<cv::Rect>;
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using GSize = cv::GOpaque<cv::Size>;
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using GPrims = cv::GArray<cv::gapi::wip::draw::Prim>;
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G_API_OP(BBoxes, <GPrims(GDetections)>, "sample.custom.b-boxes") {
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static cv::GArrayDesc outMeta(const cv::GArrayDesc &) {
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return cv::empty_array_desc();
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}
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};
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GAPI_OCV_KERNEL(OCVBBoxes, BBoxes) {
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// This kernel converts the rectangles into G-API's
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// rendering primitives
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static void run(const std::vector<cv::Rect> &in_face_rcs,
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std::vector<cv::gapi::wip::draw::Prim> &out_prims) {
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out_prims.clear();
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const auto cvt = [](const cv::Rect &rc, const cv::Scalar &clr) {
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return cv::gapi::wip::draw::Rect(rc, clr, 2);
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};
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for (auto &&rc : in_face_rcs) {
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out_prims.emplace_back(cvt(rc, CV_RGB(0,255,0))); // green
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}
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}
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};
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} // namespace custom
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int main(int argc, char *argv[]) {
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cv::CommandLineParser cmd(argc, argv, keys);
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if (cmd.has("help")) {
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cmd.printMessage();
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return 0;
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}
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const auto det_name = cmd.get<std::string>("detector");
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const auto duration = cmd.get<int>("duration");
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if (det_name.empty()) {
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std::cerr << "FATAL: path to detection model is not provided for the sample."
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<< "Please specify it with --detector options."
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<< std::endl;
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return 1;
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}
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// Prepare G-API kernels and networks packages:
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auto detector = cv::gapi::oak::Params<custom::FaceDetector>(det_name);
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auto networks = cv::gapi::networks(detector);
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auto kernels = cv::gapi::combine(
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cv::gapi::kernels<custom::OCVBBoxes>(),
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cv::gapi::oak::kernels());
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auto args = cv::compile_args(kernels, networks);
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// Initialize graph structure
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cv::GFrame in;
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cv::GFrame copy = cv::gapi::oak::copy(in); // NV12 transfered to host + passthrough copy for infer
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cv::GOpaque<cv::Size> sz = cv::gapi::streaming::size(copy);
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// infer is not affected by the actual copy here
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cv::GMat blob = cv::gapi::infer<custom::FaceDetector>(copy);
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// FIXME: OAK infer detects faces slightly out of frame bounds
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cv::GArray<cv::Rect> rcs = cv::gapi::parseSSD(blob, sz, 0.5f, true, false);
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auto rendered = cv::gapi::wip::draw::renderFrame(copy, custom::BBoxes::on(rcs));
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// on-the-fly conversion NV12->BGR
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cv::GMat out = cv::gapi::streaming::BGR(rendered);
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auto pipeline = cv::GComputation(cv::GIn(in), cv::GOut(out, rcs))
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.compileStreaming(std::move(args));
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// Graph execution
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pipeline.setSource(cv::gapi::wip::make_src<cv::gapi::oak::ColorCamera>());
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pipeline.start();
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cv::Mat out_mat;
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std::vector<cv::Rect> out_dets;
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int frames = 0;
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while (pipeline.pull(cv::gout(out_mat, out_dets))) {
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std::string name = "oak_infer_frame_" + std::to_string(frames) + ".png";
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cv::imwrite(name, out_mat);
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if (!out_dets.empty()) {
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std::cout << "Got " << out_dets.size() << " detections on frame #" << frames << std::endl;
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}
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++frames;
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if (frames == duration) {
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pipeline.stop();
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break;
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}
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}
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std::cout << "Pipeline finished. Processed " << frames << " frames" << std::endl;
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return 0;
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}
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