object 如何在 ROS 上使用 yolov4 和 opencv dnn 進行檢測？

Question

我想在 ROS 平台上使用 YOLOv4 的 OpenCV DNN 模塊檢測 object 但它不起作用。 但是，我在沒有 ROS 平台的情況下運行了 yolov4 的 opencv dnn 模塊。 相同的代碼片段在 ROS 平台上不起作用。

CMakeList.txt：（我鏈接了OpenCV）

cmake_minimum_required(VERSION 3.0.2)
project(test_opencv)
  
set(CMAKE_CXX_STANDARD_REQUIRED 17)
add_compile_options(--std=c++17 -g3)
set(OpenCV_DIR "/home/usernamepc/opencv_build/opencv/build")

find_package(OpenCV 4.4.0 REQUIRED)

我的代碼在這里。 此代碼在沒有 ROS 的情況下工作，但不適用於 ROS。

int main(int argc, char **argv){

ros::init(argc, argv, "test_opencv");

int inpWidth = 608;
int inpHeight = 608;
int count = 0;
std::cout << "OpenCV version : " << CV_VERSION << std::endl;
std::cout << "Major version : " << CV_MAJOR_VERSION << std::endl;
std::cout << "Minor version : " << CV_MINOR_VERSION << std::endl;
std::cout << "Subminor version : " << CV_SUBMINOR_VERSION << std::endl;

vector<string> class_names;
{
    ifstream class_file("/home/USERNAMEPC/people_detection_ws/src/test_opencv/input/data/obj_license.names");

    if (!class_file)
    {
        cerr << "failed to open classes.txt\n";
        return 0;
    }

    string line;
    while (getline(class_file, line))
    {
        class_names.push_back(line);
        cout << "Data: " << line << endl;
    }
}
string video = "/home/USERNAMEPC/people_detection_ws/src/test_opencv/input/plate/1.mp4";
VideoCapture cap(video); 
auto net = readNetFromDarknet("/home/USERNAMEPC/people_detection_ws/src/test_opencv/input/cfg/yolov4_obj_license.cfg",
                              "/home/USERNAMEPC/people_detection_ws/src/test_opencv/input/custom_license.weights");

auto output_names = net.getUnconnectedOutLayersNames();
double inference_fps = 0;
double total_fps = 0;

Mat frame, blob;
vector<Mat> detections;
while (waitKey(1) < 1)
{

    cap >> frame;

    if (frame.empty())
    {
        waitKey();
        break;
    }
    auto total_start = chrono::steady_clock::now();

    imshow("frame", frame);
    waitKey(1);
    cv::dnn::blobFromImage(frame, blob, 0.00392, Size(inpWidth, inpHeight), Scalar(), true, false, CV_32F);

    net.setInput(blob);
    if (blob.empty())
    {
        std::cout << "blob is empty" << std::endl;
        return -1;
    }

    auto dnn_start = chrono::steady_clock::now();
    cout << "6 " << endl;

    net.forward(detections, output_names);

    cout << "7  " << endl;

    auto dnn_end = chrono::steady_clock::now();

    vector<int> indices[NUM_CLASSES];
    vector<Rect> boxes[NUM_CLASSES];
    vector<float> scores[NUM_CLASSES];

    for (auto &output : detections)
    {
        const auto num_boxes = output.rows;
        for (int i = 0; i < num_boxes; i++)
        {

            auto x = output.at<float>(i, 0) * frame.cols;
            auto y = output.at<float>(i, 1) * frame.rows;
            auto width = output.at<float>(i, 2) * frame.cols;
            auto height = output.at<float>(i, 3) * frame.rows;
            Rect rect(x - width / 2, y - height / 2, width, height);

            for (int c = 0; c < NUM_CLASSES; c++)
            {
                auto confidence = *output.ptr<float>(i, 5 + c);
                if (confidence >= CONFIDENCE_THRESHOLD)
                {
                    boxes[c].push_back(rect);
                    scores[c].push_back(confidence);
                    detected_control = true;
                }
            }
        }
    }

    for (int c = 0; c < NUM_CLASSES; c++)
    {
        NMSBoxes(boxes[c], scores[c], 0.0, NMS_THRESHOLD, indices[c]);
    }

    for (int c = 0; c < NUM_CLASSES; c++)
    {
        for (size_t i = 0; i < indices[c].size(); ++i)
        {

            const auto color = colors[c % NUM_COLORS];
            auto idx = indices[c][i];
            auto &rect = boxes[c][idx];
            rectangle(frame, Point(rect.x, rect.y), Point(rect.x + rect.width, rect.y + rect.height), color, 3);
            ostringstream label_ss;
            label_ss << class_names[c] << ": " << fixed << setprecision(2) << scores[c][idx];
            auto label = label_ss.str();

            int baseline;
            auto label_bg_sz = getTextSize(label.c_str(), FONT_HERSHEY_COMPLEX_SMALL, 1, 1, &baseline);
            rectangle(frame, Point(rect.x, rect.y - label_bg_sz.height - baseline - 10), Point(rect.x + label_bg_sz.width, rect.y), color, FILLED);
            putText(frame, label.c_str(), Point(rect.x, rect.y - baseline - 5), FONT_HERSHEY_COMPLEX_SMALL, 1, Scalar(0, 0, 0));
        }
    }

    auto total_end = chrono::steady_clock::now();
    inference_fps = 1000.0 / chrono::duration_cast<chrono::milliseconds>(dnn_end - dnn_start).count();
    total_fps = 1000.0 / chrono::duration_cast<chrono::milliseconds>(total_end - total_start).count();
    ostringstream stats_ss;
    stats_ss << fixed << setprecision(2);
    stats_ss << "Inference FPS: " << inference_fps << ", Total FPS: " << total_fps;
    auto stats = stats_ss.str();

    int baseline;
    auto stats_bg_sz = getTextSize(stats.c_str(), FONT_HERSHEY_COMPLEX_SMALL, 1, 1, &baseline);
    rectangle(frame, Point(0, 0), Point(stats_bg_sz.width, stats_bg_sz.height + 10), Scalar(0, 0, 0), FILLED);
    putText(frame, stats.c_str(), Point(0, stats_bg_sz.height + 5), FONT_HERSHEY_COMPLEX_SMALL, 1, Scalar(255, 255, 255));
    // namedWindow("output");
    count++;
}

cout << "Inference FPS: " << inference_fps << ", Total FPS: " << total_fps << endl;

ros::spin();

return 0; }

代碼執行步驟時出現錯誤

net.forward（檢測，輸出名稱）；

錯誤如下：

OpenCV 錯誤：斷言失敗 (dims <= 2) in reshape，文件 /build/opencv-L2vuMj/opencv-3.2.0+dfsg/modules/core/src/matrix.cpp，第 1032 行終止在拋出一個實例后調用cv::Exception' what(): /build/opencv-L2vuMj/opencv-3.2.0+dfsg/modules/core/src/matrix.cpp:1032: error: (-215) dims <= 2 in function reshape

當我使用 GDB 調試器時，我得到 output 的錯誤，如下所示：

(gdb) bt #0 0x00007ffff61b5e87 in __GI_raise (sig=sig@entry=6) at../sysdeps/unix/sysv/linux/raise.c:51

#1 0x00007ffff61b77f1 in __GI_abort () at abort.c:79

#2 0x00007ffff680c957 in () at /usr/lib/x86_64-linux-gnu/libstdc++.so.6

#3 0x00007ffff6812ae6 in () at /usr/lib/x86_64-linux-gnu/libstdc++.so.6

#4 0x00007ffff6812b21 in () at /usr/lib/x86_64-linux-gnu/libstdc++.so.6

#5 0x00007ffff6812d54 in () at /usr/lib/x86_64-linux-gnu/libstdc++.so.6

#6 0x00007ffff77c38a2 in cv::error(cv::Exception const&) () at /usr/lib/x86_64-linux-gnu/libopencv_core.so.3.2

#7 0x00007ffff77c39bf in cv::error(int, cv::String const&, char const*, char const*, int) () at /usr/lib/x86_64-linux-gnu/libopencv_core.so.3.2

#8 0x00007ffff7734b1c in cv::Mat::reshape(int, int) const () at /usr/lib/x86_64-linux-gnu/libopencv_core.so.3.2

#9 0x00007ffff6efb344 in cv::dnn::ConvolutionLayerImpl::finalize(cv::_InputArray const&, cv::_OutputArray const&) () 在 /home/USERNAMEPC/opencv_build/opencv/build/lib/libopencv_dnn.so.4.4

#10 0x00007ffff6eb12d7 in cv::dnn::dnn4_v20200609::Layer::finalize(std::vector<cv::Mat, std::allocator<cv::Mat> > const&, std::vector<cv::Mat , std::allocator<cv::Mat> >&) () 在 /home/USERNAMEPC/opencv_build/opencv/build/lib/libopencv_dnn.so.4.4

#11 0x00007ffff6ed1ff3 in cv::dnn::dnn4_v20200609::Net::Impl::allocateLayer(int, std::map<int, cv::dnn::dnn4_v20200609::(匿名命名空間)::LayerShapes, std::更少，std::allocator<std::pair<int const, cv::dnn::dnn4_v20200609::(匿名命名空間)::LayerShapes>> const&) () at /home/USERNAMEPC/opencv_build/opencv/build/ lib/libopencv_dnn.so.4.4

#12 0x00007ffff6ed3ff2 in cv::dnn::dnn4_v20200609::Net::Impl::allocateLayers(std::vector<cv::dnn::dnn4_v20200609::LayerPin, std::allocator<cv::dnn::dnn4_v20200609: :LayerPin> > const&) () 在/home/USERNAMEPC/opencv_build/opencv/build/lib/libopencv_dnn.so.4.4

#13 0x00007ffff6ed7675 in cv::dnn::dnn4_v20200609::Net::Impl::setUpNet(std::vector<cv::dnn::dnn4_v20200609::LayerPin, std::allocator<cv::dnn::dnn4_v20200609: :LayerPin> > const&) () 在/home/USERNAMEPC/opencv_build/opencv/build/lib/libopencv_dnn.so.4.4

#14 0x00007ffff6ed8ac3 in cv::dnn::dnn4_v20200609::Net::forward(cv::_OutputArray const&, std::vector<std::__cxx11::basic_string<char, std::char_traits, std::allocator >, std::allocator<std::__cxx11::basic_string<char, std::char_traits, std::allocator > > > const&) () at /home/USERNAMEPC/opencv_build/opencv/build/lib/libopencv_dnn.so.4.4

#15 0x0000555555561c0e 在 main(int, char**) (argc=1, argv=0x7fffffffd918) 在 /home/USERNAMEPC/people_detection_ws/src/test_opencv/src/test_opencv.cpp:147

我怎么解決這個問題？

Answer 1

我刪除cv_bridge並從 github 上的源代碼安裝。 一天結束，代碼正在運行。