add color line detection and supplementary files
This commit is contained in:
lxm
parent
e21327dd71
commit
f9eb5c3205
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@ -69,6 +69,7 @@ include_directories(
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${CMAKE_CURRENT_SOURCE_DIR}/algorithm/common_det/cuda
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${CMAKE_CURRENT_SOURCE_DIR}/algorithm/landing_det/cuda
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${CMAKE_CURRENT_SOURCE_DIR}/algorithm/tracking/ocv470
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${CMAKE_CURRENT_SOURCE_DIR}/algorithm/color_line
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${CMAKE_CURRENT_SOURCE_DIR}/video_io
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${CMAKE_CURRENT_SOURCE_DIR}/algorithm/ellipse_det
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${CMAKE_CURRENT_SOURCE_DIR}/utils
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@ -108,6 +109,7 @@ set(
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include/sv_common_det.h
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include/sv_landing_det.h
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include/sv_tracking.h
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include/sv_color_line.h
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include/sv_video_input.h
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include/sv_video_output.h
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include/sv_world.h
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@ -148,10 +150,13 @@ set(spirecv_SRCS
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algorithm/common_det/sv_common_det.cpp
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algorithm/landing_det/sv_landing_det.cpp
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algorithm/tracking/sv_tracking.cpp
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algorithm/color_line/sv_color_line.cpp
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)
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file(GLOB ALG_SRC_FILES ${CMAKE_CURRENT_SOURCE_DIR}/algorithm/tracking/ocv470/*.cpp)
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list(APPEND spirecv_SRCS ${ALG_SRC_FILES})
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file(GLOB ALG_SRC_FILES ${CMAKE_CURRENT_SOURCE_DIR}/algorithm/color_line/*.cpp)
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list(APPEND spirecv_SRCS ${ALG_SRC_FILES})
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file(GLOB ALG_SRC_FILES ${CMAKE_CURRENT_SOURCE_DIR}/video_io/*.cpp)
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list(APPEND spirecv_SRCS ${ALG_SRC_FILES})
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file(GLOB ALG_SRC_FILES ${CMAKE_CURRENT_SOURCE_DIR}/utils/*.cpp)
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@ -237,7 +242,7 @@ elseif(PLATFORM STREQUAL "X86_CPU")
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endif()
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endif()
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#demo
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add_executable(ArucoDetection samples/demo/aruco_detection.cpp)
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target_link_libraries(ArucoDetection sv_world)
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add_executable(CameraReading samples/demo/camera_reading.cpp)
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@ -252,6 +257,8 @@ add_executable(LandingMarkerDetection samples/demo/landing_marker_detection.cpp)
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target_link_libraries(LandingMarkerDetection sv_world)
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add_executable(SingleObjectTracking samples/demo/single_object_tracking.cpp)
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target_link_libraries(SingleObjectTracking sv_world)
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add_executable(ColorLineDetection samples/demo/color_line_detect.cpp)
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target_link_libraries(ColorLineDetection sv_world)
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add_executable(UdpDetectionInfoReceiver samples/demo/udp_detection_info_receiver.cpp)
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target_link_libraries(UdpDetectionInfoReceiver sv_world)
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add_executable(UdpDetectionInfoSender samples/demo/udp_detection_info_sender.cpp)
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@ -260,12 +267,17 @@ add_executable(VideoSaving samples/demo/video_saving.cpp)
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target_link_libraries(VideoSaving sv_world)
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add_executable(VideoStreaming samples/demo/video_streaming.cpp)
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target_link_libraries(VideoStreaming sv_world)
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add_executable(GimbalClickedTracking samples/demo/gimbal_detection_with_clicked_tracking.cpp)
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target_link_libraries(GimbalClickedTracking sv_world)
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add_executable(GimbalLandingMarkerDetection samples/demo/gimbal_landing_marker_detection.cpp)
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target_link_libraries(GimbalLandingMarkerDetection sv_world)
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add_executable(GimbalUdpDetectionInfoSender samples/demo/gimbal_udp_detection_info_sender.cpp)
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target_link_libraries(GimbalUdpDetectionInfoSender sv_world)
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include_directories(${CMAKE_CURRENT_SOURCE_DIR}/samples/calib)
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add_executable(CameraCalibrarion samples/calib/calibrate_camera_charuco.cpp)
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target_link_libraries(CameraCalibrarion ${OpenCV_LIBS})
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message(STATUS "CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
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if (NOT DEFINED SV_INSTALL_PREFIX)
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set(SV_INSTALL_PREFIX ${CMAKE_INSTALL_PREFIX})
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@ -10,7 +10,7 @@ SpireCV是一个专为**智能无人系统**打造的**边缘实时感知SDK**
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## 快速入门
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- 安装及使用：[SpireCV使用手册](https://wiki.amovlab.com/public/spirecv-wiki/)
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- 安装及使用：[SpireCV使用手册](https://www.wolai.com/4qWFM6aZmtpQE6jj7hnNMW)
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- 需掌握C++语言基础、CMake编译工具基础。
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- 需要掌握OpenCV视觉库基础，了解CUDA、OpenVINO、RKNN和CANN等计算库。
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- 需要了解ROS基本概念及基本操作。
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@ -0,0 +1,252 @@
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#include "sv_color_line.h"
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#include "gason.h"
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#include "sv_util.h"
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#include <cmath>
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#include <fstream>
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namespace sv {
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ColorLineDetector::ColorLineDetector()
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{
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this->is_load_parameter = false;
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}
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ColorLineDetector::~ColorLineDetector()
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{
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}
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void ColorLineDetector::_load()
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{
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JsonValue all_value;
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JsonAllocator allocator;
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_load_all_json(this->alg_params_fn, all_value, allocator);
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JsonValue colorliner_params_value;
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_parser_algorithm_params("ColorLineDetector", all_value, colorliner_params_value);
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for (auto i : colorliner_params_value) {
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if ("line_color" == std::string(i->key)) {
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this->line_color = i->value.toString();
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std::cout << "line_color: " << this->line_color << std::endl;
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}
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else if ("line_location" == std::string(i->key)) {
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this->line_location = i->value.toNumber();
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}
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else if ("line_location_a1" == std::string(i->key)) {
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this->line_location_a1 = i->value.toNumber();
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}
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else if ("line_location_a2" == std::string(i->key)) {
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this->line_location_a2 = i->value.toNumber();
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}
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}
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}
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void ColorLineDetector::get_line_area(cv::Mat &frame, cv::Mat &line_area, cv::Mat &line_area_a1, cv::Mat &line_area_a2) {
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int h = frame.rows;
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half_h = h / 2.0;
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half_w = frame.cols / 2.0;
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int l1 = int(h * (1 - line_location - 0.05));
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int l2 = int(h * (1 - line_location));
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line_area = frame(cv::Range(l1, l2), cv::Range::all());
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l1 = int(h * (1 - line_location_a1 - 0.05));
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l2 = int(h * (1 - line_location_a1));
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line_area_a1 = frame(cv::Range(l1, l2), cv::Range::all());
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cy_a1 = l1;
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l1 = int(h * (1 - line_location_a2 - 0.05));
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l2 = int(h * (1 - line_location_a2));
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cy_a2 = l1;
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line_area_a2 = frame(cv::Range(l1, l2), cv::Range::all());
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}
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float ColorLineDetector::cnt_area(std::vector<cv::Point> cnt) {
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float area = cv::contourArea(cnt);
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return area;
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}
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void ColorLineDetector::seg(cv::Mat line_area, cv::Mat line_area_a1, cv::Mat line_area_a2, std::string _line_color, cv::Point ¢er, int &area, cv::Point ¢er_a1, cv::Point ¢er_a2) {
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int hmin, smin, vmin, hmax, smax, vmax;
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if (_line_color == "black") {
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hmin = 0;
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smin = 0;
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vmin = 0;
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hmax = 180;
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smax = 255;
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vmax = 46;
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}
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else if (_line_color == "red") {
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hmin = 0;
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smin = 43;
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vmin = 46;
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hmax = 10;
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smax = 255;
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vmax = 255;
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}
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else if (_line_color == "yellow") {
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hmin = 26;
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smin = 43;
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vmin = 46;
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hmax = 34;
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smax = 255;
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vmax = 255;
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}
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else if (_line_color == "green") {
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hmin = 35;
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smin = 43;
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vmin = 46;
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hmax = 77;
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smax = 255;
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vmax = 255;
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}
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else if (_line_color == "blue") {
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hmin = 100;
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smin = 43;
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vmin = 46;
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hmax = 124;
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smax = 255;
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vmax = 255;
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}
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else {
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hmin = 0;
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smin = 0;
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vmin = 0;
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hmax = 180;
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smax = 255;
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vmax = 46;
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}
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cv::cvtColor(line_area, line_area, cv::COLOR_BGR2HSV);
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cv::inRange(line_area, cv::Scalar(hmin, smin, vmin), cv::Scalar(hmax, smax, vmax), line_area);
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cv::Mat kernel = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(5, 5));
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cv::morphologyEx(line_area, line_area, cv::MORPH_OPEN, kernel);
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std::vector<std::vector<cv::Point>> contours;
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std::vector<cv::Vec4i> hierarchy;
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cv::findContours(line_area, contours, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
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if (contours.size() > 0) {
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cv::Rect rect = cv::boundingRect(contours[0]);
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int cx = rect.x + rect.width / 2;
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int cy = rect.y + rect.height / 2;
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std::sort(contours.begin(), contours.end(),[](const std::vector<cv::Point>& a, const std::vector<cv::Point>& b) {return cv::contourArea(a) > cv::contourArea(b);});
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area = cnt_area(contours[0]);
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center = cv::Point(cx, cy);
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}
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cv::cvtColor(line_area_a1, line_area_a1, cv::COLOR_BGR2HSV);
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cv::inRange(line_area_a1, cv::Scalar(hmin, smin, vmin), cv::Scalar(hmax, smax, vmax), line_area_a1);
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//cv2.MORPH_CLOSE 先进行膨胀，再进行腐蚀操作
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kernel = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(5, 5));
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cv::morphologyEx(line_area_a1, line_area_a1, cv::MORPH_CLOSE, kernel);
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std::vector<std::vector<cv::Point>> contours_a1;
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cv::findContours(line_area_a1, contours_a1, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
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if (contours_a1.size() > 0) {
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cv::Rect rect = cv::boundingRect(contours_a1[0]);
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int cx = rect.x + rect.width / 2;
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int cy = rect.y + rect.height / 2 + cy_a1;
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center_a1 = cv::Point(cx - half_w, cy - half_h);
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}
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cv::cvtColor(line_area_a2, line_area_a2, cv::COLOR_BGR2HSV);
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cv::inRange(line_area_a2, cv::Scalar(hmin, smin, vmin), cv::Scalar(hmax, smax, vmax), line_area_a2);
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kernel = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(5, 5));
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cv::morphologyEx(line_area_a2, line_area_a2, cv::MORPH_CLOSE, kernel);
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std::vector<std::vector<cv::Point>> contours_a2;
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cv::findContours(line_area_a2, contours_a2, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
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if (contours_a2.size() > 0) {
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cv::Rect rect = cv::boundingRect(contours_a2[0]);
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int cx = rect.x + rect.width / 2;
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int cy = rect.y + rect.height / 2 + cy_a2;
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center_a2 = cv::Point(cx - half_w, cy - half_h);
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}
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}
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void ColorLineDetector::detect(cv::Mat img, sv::TargetsInFrame& tgts_)
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{
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if(!this->is_load_parameter)
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{
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_load();
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this->is_load_parameter = true;
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}
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int area_n = -1;
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cv::Mat area_base, area_base_a1, area_base_a2;
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cv::Point cxcy_n(0, 0), center_a1_n(0,0), center_a2_n(0, 0);
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get_line_area(img, area_base, area_base_a1, area_base_a2);
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seg(area_base, area_base_a1, area_base_a2, line_color, cxcy_n, area_n, center_a1_n, center_a2_n);
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pose.x = 0.0;
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pose.y = -1.0;
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pose.z = 0.0;
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if (area_n > 0)
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{
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circle(area_base, cv::Point(cxcy_n.x, cxcy_n.y), 4, cv::Scalar(0, 0, 255), -1);
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double angle = (cxcy_n.x - this->camera_matrix.at<double>(0, 2)) / this->camera_matrix.at<double>(0, 2) * atan((double)(area_base.rows / 2) / this->fov_x);
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pose.x = angle;
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pose.y = 1.0;
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}
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else
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{
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cv::Point cxcy__n(0, 0), center_a1__n(0, 0), center_a2__n(0, 0);
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seg(area_base, area_base_a1, area_base_a2, line_color, cxcy__n, area_n = 0, center_a1__n, center_a2__n);
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if (area_n > 0)
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{
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circle(area_base, cv::Point(cxcy_n.x, cxcy_n.y), 4, cv::Scalar(0, 0, 255), -1);
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double angle = (cxcy_n.x - this->camera_matrix.at<double>(0, 2)) / this->camera_matrix.at<double>(0, 2) * atan((double)(area_base.rows / 2) / this->fov_x);
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pose.x = angle;
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pose.y = 1.0;
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pose.z = 0.0;
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}
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}
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tgts_.setSize(img.cols, img.rows);
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tgts_.setFOV(this->fov_x, this->fov_y);
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auto t1 = std::chrono::system_clock::now();
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tgts_.setFPS(1000.0/std::chrono::duration_cast<std::chrono::milliseconds>(t1- this->_t0).count());
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this->_t0 = std::chrono::system_clock::now();
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tgts_.setTimeNow();
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if(area_n > 0)
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{
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Target tgt;
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tgt.los_ax = pose.x;
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if(cxcy_n.x !=0 || cxcy_n.y !=0)
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{
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tgt.cx = cxcy_n.x;
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tgt.cy = cxcy_n.y;
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}
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else if(center_a1_n.x != 0 || center_a1_n.y != 0)
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{
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tgt.cx = center_a1_n.x;
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tgt.cy = center_a1_n.y;
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}
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else if(center_a2_n.x != 0 || center_a2_n.y != 0)
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{
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tgt.cx = center_a2_n.x;
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tgt.cy = center_a2_n.y;
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}
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tgts_.targets.push_back(tgt);
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}
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}
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}
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@ -0,0 +1,48 @@
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#ifndef __SV_COLOR_LINE__
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#define __SV_COLOR_LINE__
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#include "sv_core.h"
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#include <opencv2/opencv.hpp>
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#include <string>
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#include <chrono>
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namespace sv {
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class ColorLineDetector : public CameraAlgorithm
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{
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public:
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ColorLineDetector();
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~ColorLineDetector();
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void detect(cv::Mat img_, TargetsInFrame& tgts_);
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protected:
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float cy_a1;
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float cy_a2;
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float half_h;
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float half_w;
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cv::Mat img;
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cv::Point3d pose;
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double line_location;
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double line_location_a1;
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double line_location_a2;
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bool is_load_parameter;
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std::string line_color;
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void _load();
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float cnt_area(std::vector<cv::Point> cnt);
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void get_line_area(cv::Mat &frame, cv::Mat &line_area, cv::Mat &line_area_a1, cv::Mat &line_area_a2);
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void seg(cv::Mat line_area, cv::Mat line_area_a1, cv::Mat line_area_a2, std::string _line_color, cv::Point ¢er, int &area, cv::Point ¢er_a1, cv::Point ¢er_a2);
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};
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}
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#endif
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@ -5,6 +5,7 @@
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#include "sv_common_det.h"
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#include "sv_landing_det.h"
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#include "sv_tracking.h"
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#include "sv_color_line.h"
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#include "sv_video_input.h"
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#include "sv_video_output.h"
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@ -0,0 +1,185 @@
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{
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"CommonObjectDetector": {
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"dataset": "COCO",
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"inputSize": 640,
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"nmsThrs": 0.6,
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"scoreThrs": 0.4,
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"useWidthOrHeight": 1,
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"withSegmentation": true,
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"datasetPersonVehicle": {
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"person": [0.5, 1.8],
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"car": [4.1, 1.5],
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"bus": [10, 3],
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"truck": [-1, -1],
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"bike": [-1, -1],
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"train": [-1, -1],
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"boat": [-1, -1],
|
||||
"aeroplane": [-1, -1]
|
||||
},
|
||||
"datasetDrone": {
|
||||
"drone": [0.4, 0.2]
|
||||
},
|
||||
"datasetCOCO": {
|
||||
"person": [-1, -1],
|
||||
"bicycle": [-1, -1],
|
||||
"car": [-1, -1],
|
||||
"motorcycle": [-1, -1],
|
||||
"airplane": [-1, -1],
|
||||
"bus": [-1, -1],
|
||||
"train": [-1, -1],
|
||||
"truck": [-1, -1],
|
||||
"boat": [-1, -1],
|
||||
"traffic light": [-1, -1],
|
||||
"fire hydrant": [-1, -1],
|
||||
"stop sign": [-1, -1],
|
||||
"parking meter": [-1, -1],
|
||||
"bench": [-1, -1],
|
||||
"bird": [-1, -1],
|
||||
"cat": [-1, -1],
|
||||
"dog": [-1, -1],
|
||||
"horse": [-1, -1],
|
||||
"sheep": [-1, -1],
|
||||
"cow": [-1, -1],
|
||||
"elephant": [-1, -1],
|
||||
"bear": [-1, -1],
|
||||
"zebra": [-1, -1],
|
||||
"giraffe": [-1, -1],
|
||||
"backpack": [-1, -1],
|
||||
"umbrella": [-1, -1],
|
||||
"handbag": [-1, -1],
|
||||
"tie": [-1, -1],
|
||||
"suitcase": [-1, -1],
|
||||
"frisbee": [-1, -1],
|
||||
"skis": [-1, -1],
|
||||
"snowboard": [-1, -1],
|
||||
"sports ball": [-1, -1],
|
||||
"kite": [-1, -1],
|
||||
"baseball bat": [-1, -1],
|
||||
"baseball glove": [-1, -1],
|
||||
"skateboard": [-1, -1],
|
||||
"surfboard": [-1, -1],
|
||||
"tennis racket": [-1, -1],
|
||||
"bottle": [-1, -1],
|
||||
"wine glass": [-1, -1],
|
||||
"cup": [-1, -1],
|
||||
"fork": [-1, -1],
|
||||
"knife": [-1, -1],
|
||||
"spoon": [-1, -1],
|
||||
"bowl": [-1, -1],
|
||||
"banana": [-1, -1],
|
||||
"apple": [-1, -1],
|
||||
"sandwich": [-1, -1],
|
||||
"orange": [-1, -1],
|
||||
"broccoli": [-1, -1],
|
||||
"carrot": [-1, -1],
|
||||
"hot dog": [-1, -1],
|
||||
"pizza": [-1, -1],
|
||||
"donut": [-1, -1],
|
||||
"cake": [-1, -1],
|
||||
"chair": [-1, -1],
|
||||
"couch": [-1, -1],
|
||||
"potted plant": [-1, -1],
|
||||
"bed": [-1, -1],
|
||||
"dining table": [-1, -1],
|
||||
"toilet": [-1, -1],
|
||||
"tv": [-1, -1],
|
||||
"laptop": [-1, -1],
|
||||
"mouse": [-1, -1],
|
||||
"remote": [-1, -1],
|
||||
"keyboard": [-1, -1],
|
||||
"cell phone": [-1, -1],
|
||||
"microwave": [-1, -1],
|
||||
"oven": [-1, -1],
|
||||
"toaster": [-1, -1],
|
||||
"sink": [-1, -1],
|
||||
"refrigerator": [-1, -1],
|
||||
"book": [-1, -1],
|
||||
"clock": [-1, -1],
|
||||
"vase": [-1, -1],
|
||||
"scissors": [-1, -1],
|
||||
"teddy bear": [-1, -1],
|
||||
"hair drier": [-1, -1],
|
||||
"toothbrush": [-1, -1]
|
||||
}
|
||||
},
|
||||
"AutoFocusObjectDetector": {
|
||||
"lock_thres": 5,
|
||||
"unlock_thres": 5,
|
||||
"lock_scale_init": 12.0,
|
||||
"lock_scale": 8.0,
|
||||
"categories_filter": [],
|
||||
"keep_unlocked": false,
|
||||
"use_square_region": false
|
||||
},
|
||||
"SingleObjectTracker": {
|
||||
"algorithm": "nano",
|
||||
"backend": 0,
|
||||
"target": 0
|
||||
},
|
||||
"LandingMarkerDetector": {
|
||||
"labels": ["h"],
|
||||
"maxCandidates": 5
|
||||
},
|
||||
"EllipseDetector": {
|
||||
"radiusInMeter": 0.5,
|
||||
"preProcessingGaussKernel": 5,
|
||||
"preProcessingGaussSigma": 1.306,
|
||||
"thPosition": 1.0,
|
||||
"maxCenterDistance": 0.05,
|
||||
"minEdgeLength": 9,
|
||||
"minOrientedRectSide": 2.984,
|
||||
"distanceToEllipseContour": 0.111,
|
||||
"minScore": 0.511,
|
||||
"minReliability": 0.470,
|
||||
"ns": 22,
|
||||
"percentNe": 0.946,
|
||||
"T_CNC": 0.121,
|
||||
"T_TCN_L": 0.468,
|
||||
"T_TCN_P": 0.560,
|
||||
"thRadius": 0.202
|
||||
},
|
||||
"ArucoDetector": {
|
||||
"dictionaryId": 10,
|
||||
"markerIds": [-1],
|
||||
"markerLengths": [0.2],
|
||||
"adaptiveThreshConstant": 7,
|
||||
"adaptiveThreshWinSizeMax": 23,
|
||||
"adaptiveThreshWinSizeMin": 3,
|
||||
"adaptiveThreshWinSizeStep": 10,
|
||||
"aprilTagCriticalRad": 0.17453292519,
|
||||
"aprilTagDeglitch": 0,
|
||||
"aprilTagMaxLineFitMse": 10.0,
|
||||
"aprilTagMaxNmaxima": 10,
|
||||
"aprilTagMinClusterPixels": 5,
|
||||
"aprilTagMinWhiteBlackDiff": 5,
|
||||
"aprilTagQuadDecimate": 0.0,
|
||||
"aprilTagQuadSigma": 0.0,
|
||||
"cornerRefinementMaxIterations": 30,
|
||||
"cornerRefinementMethod": 0,
|
||||
"cornerRefinementMinAccuracy": 0.1,
|
||||
"cornerRefinementWinSize": 5,
|
||||
"detectInvertedMarker": false,
|
||||
"errorCorrectionRate": 0.6,
|
||||
"markerBorderBits": 1,
|
||||
"maxErroneousBitsInBorderRate": 0.35,
|
||||
"maxMarkerPerimeterRate": 4.0,
|
||||
"minCornerDistanceRate": 0.05,
|
||||
"minDistanceToBorder": 3,
|
||||
"minMarkerDistanceRate": 0.05,
|
||||
"minMarkerLengthRatioOriginalImg": 0,
|
||||
"minMarkerPerimeterRate": 0.03,
|
||||
"minOtsuStdDev": 5.0,
|
||||
"minSideLengthCanonicalImg": 32,
|
||||
"perspectiveRemoveIgnoredMarginPerCell": 0.13,
|
||||
"perspectiveRemovePixelPerCell": 4,
|
||||
"polygonalApproxAccuracyRate": 0.03,
|
||||
"useAruco3Detection": false
|
||||
},
|
||||
"ColorLineDetector": {
|
||||
"line_color": "black",
|
||||
"line_location": 0.5,
|
||||
"line_location_a1": 0.3,
|
||||
"line_location_a2": 0.7,
|
||||
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
%YAML:1.0
|
||||
---
|
||||
calibration_time: "2021年01月12日 星期二 18时08分01秒"
|
||||
image_width: 1280
|
||||
image_height: 720
|
||||
flags: 0
|
||||
camera_matrix: !!opencv-matrix
|
||||
rows: 3
|
||||
cols: 3
|
||||
dt: d
|
||||
data: [ 7.9379415710551370e+02, 0., 2.9783879354295328e+02, 0.,
|
||||
7.9491985564466654e+02, 3.0942416136837386e+02, 0., 0., 1. ]
|
||||
distortion_coefficients: !!opencv-matrix
|
||||
rows: 1
|
||||
cols: 5
|
||||
dt: d
|
||||
data: [ 2.0950200339181715e-01, -1.1587468096518483e+00,
|
||||
5.5342063671841328e-03, 2.2214393775334758e-04,
|
||||
1.7127431916651392e+00 ]
|
||||
avg_reprojection_error: 2.8342964851391211e-01
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
%YAML:1.0
|
||||
---
|
||||
calibration_time: "2021年01月12日 星期二 18时08分01秒"
|
||||
image_width: 1920
|
||||
image_height: 1080
|
||||
flags: 0
|
||||
camera_matrix: !!opencv-matrix
|
||||
rows: 3
|
||||
cols: 3
|
||||
dt: d
|
||||
data: [ 7.9379415710551370e+02, 0., 2.9783879354295328e+02, 0.,
|
||||
7.9491985564466654e+02, 3.0942416136837386e+02, 0., 0., 1. ]
|
||||
distortion_coefficients: !!opencv-matrix
|
||||
rows: 1
|
||||
cols: 5
|
||||
dt: d
|
||||
data: [ 2.0950200339181715e-01, -1.1587468096518483e+00,
|
||||
5.5342063671841328e-03, 2.2214393775334758e-04,
|
||||
1.7127431916651392e+00 ]
|
||||
avg_reprojection_error: 2.8342964851391211e-01
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
%YAML:1.0
|
||||
---
|
||||
calibration_time: "2021年01月12日 星期二 18时08分01秒"
|
||||
image_width: 640
|
||||
image_height: 480
|
||||
flags: 0
|
||||
camera_matrix: !!opencv-matrix
|
||||
rows: 3
|
||||
cols: 3
|
||||
dt: d
|
||||
data: [ 7.9379415710551370e+02, 0., 2.9783879354295328e+02, 0.,
|
||||
7.9491985564466654e+02, 3.0942416136837386e+02, 0., 0., 1. ]
|
||||
distortion_coefficients: !!opencv-matrix
|
||||
rows: 1
|
||||
cols: 5
|
||||
dt: d
|
||||
data: [ 2.0950200339181715e-01, -1.1587468096518483e+00,
|
||||
5.5342063671841328e-03, 2.2214393775334758e-04,
|
||||
1.7127431916651392e+00 ]
|
||||
avg_reprojection_error: 2.8342964851391211e-01
|
||||
|
|
@ -0,0 +1,69 @@
|
|||
#include <iostream>
|
||||
#include <string>
|
||||
// 包含SpireCV SDK头文件
|
||||
#include <sv_world.h>
|
||||
|
||||
using namespace std;
|
||||
using namespace sv;
|
||||
|
||||
|
||||
|
||||
int main(int argc, char *argv[]) {
|
||||
// 实例化 圆形降落标志 检测器类
|
||||
sv::ColorLineDetector cld;
|
||||
// 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
|
||||
cld.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
|
||||
|
||||
// 打开摄像头
|
||||
sv::Camera cap;
|
||||
cap.setWH(640, 480);
|
||||
//cap.setFps(30);
|
||||
cap.open(sv::CameraType::WEBCAM, 0); // CameraID 0
|
||||
// 实例化OpenCV的Mat类，用于内存单帧图像
|
||||
cv::Mat img;
|
||||
int frame_id = 0;
|
||||
while (1)
|
||||
{
|
||||
// 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
cap.read(img);
|
||||
cv::resize(img, img, cv::Size(cld.image_width, cld.image_height));
|
||||
|
||||
// 执行 降落标志 检测
|
||||
cld.detect(img, tgts);
|
||||
// 可视化检测结果，叠加到img上
|
||||
sv::drawTargetsInFrame(img, tgts);
|
||||
|
||||
// 控制台打印 降落标志 检测结果
|
||||
printf("Frame-[%d]\n", frame_id);
|
||||
// 打印当前检测的FPS
|
||||
printf(" FPS = %.2f\n", tgts.fps);
|
||||
// 打印当前相机的视场角（degree）
|
||||
printf(" FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
|
||||
// 打印当前输入图像的像素宽度和高度
|
||||
printf(" Frame Size (width, height) = (%d, %d)\n", tgts.width, tgts.height);
|
||||
for (int i=0; i<tgts.targets.size(); i++)
|
||||
{
|
||||
|
||||
// 打印每个 color_line 的中心位置，cx，cy的值域为[0, 1]，以及cx，cy的像素值
|
||||
printf(" Color Line detect Center (cx, cy) = (%.3f, %.3f), in Pixels = ((%d, %d))\n",
|
||||
tgts.targets[i].cx, tgts.targets[i].cy);
|
||||
|
||||
// 打印每个color_line的x_方向反正切值，跟相机视场相关
|
||||
printf(" Color Line detect Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
|
||||
|
||||
}
|
||||
|
||||
// 显示检测结果img
|
||||
cv::imshow("img", img);
|
||||
cv::waitKey(10);
|
||||
|
||||
}
|
||||
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
|
@ -92,7 +92,7 @@ int main(int argc, char *argv[])
|
|||
// 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
gimbal.cap.read(img);
|
||||
cap.read(img);
|
||||
cv::resize(img, img, cv::Size(cod.image_width, cod.image_height));
|
||||
|
||||
// 执行通用目标检测
|
||||
|
|
@ -159,7 +159,7 @@ int main(int argc, char *argv[])
|
|||
// 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
gimbal.cap.read(img);
|
||||
cap.read(img);
|
||||
cv::resize(img, img, cv::Size(sot.image_width, sot.image_height));
|
||||
// 开始 单目标跟踪 逻辑
|
||||
// 是否有新的目标被手动框选
|
||||
|
|
|
|||
|
|
@ -68,7 +68,7 @@ int main(int argc, char *argv[])
|
|||
// 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
gimbal.cap.read(img);
|
||||
cap.read(img);
|
||||
cv::resize(img, img, cv::Size(lmd.image_width, lmd.image_height));
|
||||
|
||||
// 执行 降落标志 检测
|
||||
|
|
@ -117,12 +117,12 @@ void onMouse(int event, int x, int y, int, void *)
|
|||
{
|
||||
if (event == cv::EVENT_LBUTTONDOWN)
|
||||
{
|
||||
gimbal.gimbal->setAngleRateEuler(0, 0.02 * (y - 720 / 2), 0.02 * (x - 1280 / 2));
|
||||
gimbal->setAngleRateEuler(0, 0.02 * (y - 720 / 2), 0.02 * (x - 1280 / 2));
|
||||
}
|
||||
if (event == cv::EVENT_RBUTTONDOWN)
|
||||
{
|
||||
gimbalNoTrack();
|
||||
gimbal.gimbal->setHome();
|
||||
gimbal->setHome();
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -47,8 +47,8 @@ int main(int argc, char *argv[])
|
|||
gimbal = new sv::Gimbal(sv::GimbalType::G1, sv::GimbalLink::SERIAL);
|
||||
// 使用 /dev/ttyUSB0 作为控制串口
|
||||
gimbal->setSerialPort("/dev/ttyUSB0");
|
||||
// 以GimableCallback作为状态回调函数启用吊舱控制
|
||||
gimbal->open(GimableCallback);
|
||||
// 以gimableCallback作为状态回调函数启用吊舱控制
|
||||
gimbal->open(gimableCallback);
|
||||
// 定义相机
|
||||
sv::Camera cap;
|
||||
// 设置相机流媒体地址为 192.168.2.64
|
||||
|
|
@ -67,7 +67,7 @@ int main(int argc, char *argv[])
|
|||
// 实例化Aruco检测器类
|
||||
sv::ArucoDetector ad;
|
||||
// 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
|
||||
ad.loadCameraParams("/home/amov/SpireCV/calib_webcam_640x480.yaml");
|
||||
ad.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
|
||||
|
||||
sv::UDPServer udp;
|
||||
// 实例化OpenCV的Mat类，用于内存单帧图像
|
||||
|
|
@ -78,7 +78,7 @@ int main(int argc, char *argv[])
|
|||
// 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
gimbal->cap.read(img);
|
||||
cap.read(img);
|
||||
|
||||
// 执行Aruco二维码检测
|
||||
ad.detect(img, tgts);
|
||||
|
|
@ -88,18 +88,9 @@ int main(int argc, char *argv[])
|
|||
tgts.pod_roll = gimbalEulerAngle[1];
|
||||
tgts.pod_yaw = gimbalEulerAngle[0];
|
||||
|
||||
tgts.has_uav_pos = true;
|
||||
tgts.longitude = 1.1234567;
|
||||
tgts.latitude = 2.2345678;
|
||||
tgts.altitude = 3.3456789;
|
||||
|
||||
tgts.has_uav_vel = true;
|
||||
tgts.uav_vx = 4;
|
||||
tgts.uav_vy = 5;
|
||||
tgts.uav_vz = 6;
|
||||
|
||||
tgts.has_ill = true;
|
||||
tgts.illumination = 7;
|
||||
tgts.has_uav_pos = false;
|
||||
tgts.has_uav_vel = false;
|
||||
tgts.has_ill = false;
|
||||
|
||||
// www.write(img, tgts);
|
||||
udp.send(tgts);
|
||||
|
|
@ -118,10 +109,10 @@ void onMouse(int event, int x, int y, int, void *)
|
|||
{
|
||||
if (event == cv::EVENT_LBUTTONDOWN)
|
||||
{
|
||||
gimbal->gimbal->setAngleRateEuler(0, 0.02 * (y - 720 / 2), 0.02 * (x - 1280 / 2));
|
||||
gimbal->setAngleRateEuler(0, 0.02 * (y - 720 / 2), 0.02 * (x - 1280 / 2));
|
||||
}
|
||||
if (event == cv::EVENT_RBUTTONDOWN)
|
||||
{
|
||||
gimbal->gimbal->setHome();
|
||||
gimbal->setHome();
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -12,7 +12,6 @@ if [ ! -d ${root_dir} ]; then
|
|||
fi
|
||||
cd ${root_dir}
|
||||
|
||||
|
||||
git clone https://gitee.com/jario-jin/nv-codec-headers.git
|
||||
cd nv-codec-headers
|
||||
git checkout n11.1.5.0
|
||||
|
|
|
|||
Loading…
Reference in New Issue