Merge pull request #40 from shahurik/adas
ADAS: multiple fixes, fcw_train and fcw_detect applicationspull/73/head
Vadim Pisarevsky
11 years ago
commit
47f61f1c51
13 changed files with 919 additions and 449 deletions
@ -1,33 +1,2 @@ |
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set(name fcw_train) |
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set(the_target opencv_${name}) |
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set(the_module opencv_adas) |
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|
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ocv_check_dependencies(${OPENCV_MODULE_${the_module}_DEPS}) |
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if(NOT OCV_DEPENDENCIES_FOUND) |
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return() |
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endif() |
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project(${the_target}) |
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ocv_include_directories("${OpenCV_SOURCE_DIR}/include/opencv") |
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ocv_include_modules(${OPENCV_MODULE_${the_module}_DEPS}) |
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file(GLOB ${the_target}_SOURCES ${CMAKE_CURRENT_LIST_DIR}/*.cpp) |
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add_executable(${the_target} ${${the_target}_SOURCES}) |
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ocv_target_link_libraries(${the_target} ${OPENCV_MODULE_${the_module}_DEPS}) |
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set_target_properties(${the_target} PROPERTIES |
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DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}" |
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ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH} |
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RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH} |
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INSTALL_NAME_DIR lib |
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OUTPUT_NAME ${the_target}) |
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|
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if(ENABLE_SOLUTION_FOLDERS) |
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set_target_properties(${the_target} PROPERTIES FOLDER "applications") |
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endif() |
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install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main) |
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add_subdirectory(fcw_train) |
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add_subdirectory(fcw_detect) |
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@ -0,0 +1,35 @@ |
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set(name fcw_detect) |
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set(the_target opencv_${name}) |
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set(OPENCV_${the_target}_DEPS opencv_core opencv_imgcodecs opencv_videoio |
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opencv_highgui opencv_xobjdetect) |
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ocv_check_dependencies(${OPENCV_${the_target}_DEPS}) |
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if(NOT OCV_DEPENDENCIES_FOUND) |
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return() |
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endif() |
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project(${the_target}) |
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ocv_include_directories("${OpenCV_SOURCE_DIR}/include/opencv") |
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ocv_include_modules(${OPENCV_${the_target}_DEPS}) |
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file(GLOB ${the_target}_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp) |
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add_executable(${the_target} ${${the_target}_SOURCES}) |
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target_link_libraries(${the_target} ${OPENCV_${the_target}_DEPS}) |
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set_target_properties(${the_target} PROPERTIES |
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DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}" |
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ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH} |
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RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH} |
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INSTALL_NAME_DIR lib |
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OUTPUT_NAME ${the_target}) |
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|
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if(ENABLE_SOLUTION_FOLDERS) |
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set_target_properties(${the_target} PROPERTIES FOLDER "applications") |
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endif() |
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install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main) |
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@ -0,0 +1,92 @@ |
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#include <string> |
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using std::string; |
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#include <vector> |
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using std::vector; |
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#include <iostream> |
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using std::cerr; |
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using std::endl; |
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#include <opencv2/core.hpp> |
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using cv::Rect; |
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using cv::Size; |
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using cv::Mat; |
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using cv::Mat_; |
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using cv::Vec3b; |
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#include <opencv2/highgui.hpp> |
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using cv::imread; |
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using cv::imwrite; |
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#include <opencv2/core/utility.hpp> |
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using cv::CommandLineParser; |
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using cv::FileStorage; |
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#include <opencv2/xobjdetect.hpp> |
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using cv::xobjdetect::ICFDetector; |
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static Mat visualize(const Mat &image, const vector<Rect> &objects) |
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{ |
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CV_Assert(image.type() == CV_8UC3); |
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Mat_<Vec3b> img = image.clone(); |
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for( size_t j = 0; j < objects.size(); ++j ) |
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{ |
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Rect obj = objects[j]; |
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int x = obj.x; |
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int y = obj.y; |
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int width = obj.width; |
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int height = obj.height; |
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for( int i = y; i <= y + height; ++i ) { |
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img(i, x) = Vec3b(255, 0, 0); |
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img(i, x + width) = Vec3b(255, 0, 0); |
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} |
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for( int i = x; i <= x + width; ++i) { |
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img(y, i) = Vec3b(255, 0, 0); |
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img(y + height, i) = Vec3b(255, 0, 0); |
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} |
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} |
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return img; |
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} |
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|
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int main(int argc, char *argv[]) |
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{ |
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const string keys = |
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"{help | | print this message}" |
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"{model_filename | model.xml | filename for reading model}" |
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"{image_path | test.png | path to image for detection}" |
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"{out_image_path | out.png | path to image for output}" |
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"{threshold | 0.0 | threshold for cascade}" |
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; |
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CommandLineParser parser(argc, argv, keys); |
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parser.about("FCW detection"); |
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if( parser.has("help") || argc == 1) |
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{ |
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parser.printMessage(); |
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return 0; |
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} |
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string model_filename = parser.get<string>("model_filename"); |
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string image_path = parser.get<string>("image_path"); |
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string out_image_path = parser.get<string>("out_image_path"); |
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float threshold = parser.get<float>("threshold"); |
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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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ICFDetector detector; |
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FileStorage fs(model_filename, FileStorage::READ); |
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detector.read(fs["icfdetector"]); |
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fs.release(); |
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vector<Rect> objects; |
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Mat img = imread(image_path); |
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detector.detect(img, objects, 1.1f, Size(40, 40), |
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Size(300, 300), threshold); |
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imwrite(out_image_path, visualize(img, objects)); |
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} |
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@ -1,195 +0,0 @@ |
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#include <cstdio> |
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#include <cstring> |
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#include <string> |
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using std::string; |
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#include <vector> |
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using std::vector; |
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#include <fstream> |
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using std::ifstream; |
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using std::getline; |
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#include <sstream> |
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using std::stringstream; |
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#include <iostream> |
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using std::cerr; |
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using std::endl; |
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#include <opencv2/core.hpp> |
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using cv::Rect; |
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#include <opencv2/xobjdetect.hpp> |
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using cv::xobjdetect::ICFDetectorParams; |
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using cv::xobjdetect::ICFDetector; |
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using cv::xobjdetect::WaldBoost; |
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using cv::xobjdetect::WaldBoostParams; |
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using cv::Mat; |
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static bool read_pos_int(const char *str, int *n) |
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{ |
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int pos = 0; |
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if( sscanf(str, "%d%n", n, &pos) != 1 || str[pos] != '\0' || *n <= 0 ) |
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{ |
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return false; |
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} |
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return true; |
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} |
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static bool read_model_size(char *str, int *rows, int *cols) |
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{ |
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int pos = 0; |
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if( sscanf(str, "%dx%d%n", rows, cols, &pos) != 2 || str[pos] != '\0' || |
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*rows <= 0 || *cols <= 0) |
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{ |
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return false; |
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} |
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return true; |
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} |
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static bool read_overlap(const char *str, double *overlap) |
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{ |
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int pos = 0; |
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if( sscanf(str, "%lf%n", overlap, &pos) != 1 || str[pos] != '\0' || |
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*overlap < 0 || *overlap > 1) |
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{ |
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return false; |
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} |
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return true; |
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} |
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static bool read_labels(const string& path, |
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vector<string>& filenames, vector< vector<Rect> >& labels) |
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{ |
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string labels_path = path + "/gt.txt"; |
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string filename, line; |
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int x1, y1, x2, y2; |
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char delim; |
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ifstream ifs(labels_path.c_str()); |
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if( !ifs.good() ) |
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return false; |
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while( getline(ifs, line) ) |
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{ |
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stringstream stream(line); |
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stream >> filename; |
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filenames.push_back(path + "/" + filename); |
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vector<Rect> filename_labels; |
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while( stream >> x1 >> y1 >> x2 >> y2 >> delim ) |
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{ |
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filename_labels.push_back(Rect(x1, y1, x2, y2)); |
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} |
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labels.push_back(filename_labels); |
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filename_labels.clear(); |
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} |
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return true; |
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} |
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int main(int argc, char *argv[]) |
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{ |
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if( argc == 1 ) |
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{ |
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printf("Usage: %s OPTIONS, where OPTIONS are:\n" |
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"\n" |
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"--path <path> - path to dir with data and labels\n" |
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" (labels should have name gt.txt)\n" |
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"\n" |
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"--feature_count <count> - number of features to generate\n" |
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"\n" |
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"--weak_count <count> - number of weak classifiers in cascade\n" |
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"\n" |
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"--model_size <rowsxcols> - model size in pixels\n" |
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"\n" |
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"--overlap <measure> - number from [0, 1], means maximum\n" |
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" overlap with objects while sampling background\n" |
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"\n" |
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"--model_filename <path> - filename for saving model\n", |
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argv[0]); |
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return 0; |
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} |
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string path, model_path; |
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ICFDetectorParams params; |
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for( int i = 1; i < argc; ++i ) |
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{ |
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if( !strcmp("--path", argv[i]) ) |
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{ |
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i += 1; |
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path = argv[i]; |
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} |
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else if( !strcmp("--feature_count", argv[i]) ) |
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{ |
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i += 1; |
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if( !read_pos_int(argv[i], ¶ms.feature_count) ) |
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{ |
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fprintf(stderr, "Error reading feature count from `%s`\n", |
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argv[i]); |
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return 1; |
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} |
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} |
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else if( !strcmp("--weak_count", argv[i]) ) |
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{ |
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i += 1; |
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if( !read_pos_int(argv[i], ¶ms.weak_count) ) |
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{ |
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fprintf(stderr, "Error reading weak count from `%s`\n", |
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argv[i]); |
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return 1; |
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} |
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} |
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else if( !strcmp("--model_size", argv[i]) ) |
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{ |
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i += 1; |
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if( !read_model_size(argv[i], ¶ms.model_n_rows, |
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¶ms.model_n_cols) ) |
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{ |
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fprintf(stderr, "Error reading model size from `%s`\n", |
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argv[i]); |
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return 1; |
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} |
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} |
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else if( !strcmp("--overlap", argv[i]) ) |
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{ |
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i += 1; |
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if( !read_overlap(argv[i], ¶ms.overlap) ) |
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{ |
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fprintf(stderr, "Error reading overlap from `%s`\n", |
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argv[i]); |
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return 1; |
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} |
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} |
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else if( !strcmp("--model_filename", argv[i]) ) |
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{ |
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i += 1; |
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model_path = argv[i]; |
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} |
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else |
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{ |
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fprintf(stderr, "Error: unknown argument `%s`\n", argv[i]); |
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return 1; |
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} |
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} |
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try |
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{ |
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ICFDetector detector; |
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vector<string> filenames; |
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vector< vector<Rect> > labels; |
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read_labels(path, filenames, labels); |
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detector.train(filenames, labels, params); |
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} |
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catch( const char *err ) |
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{ |
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cerr << err << endl; |
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} |
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catch( ... ) |
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{ |
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cerr << "Unknown error\n" << endl; |
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} |
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} |
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@ -0,0 +1,35 @@ |
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set(name fcw_train) |
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set(the_target opencv_${name}) |
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set(OPENCV_${the_target}_DEPS opencv_core opencv_imgcodecs opencv_videoio |
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opencv_highgui opencv_xobjdetect) |
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ocv_check_dependencies(${OPENCV_${the_target}_DEPS}) |
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if(NOT OCV_DEPENDENCIES_FOUND) |
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return() |
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endif() |
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project(${the_target}) |
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ocv_include_directories("${OpenCV_SOURCE_DIR}/include/opencv") |
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ocv_include_modules(${OPENCV_${the_target}_DEPS}) |
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file(GLOB ${the_target}_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp) |
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add_executable(${the_target} ${${the_target}_SOURCES}) |
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target_link_libraries(${the_target} ${OPENCV_${the_target}_DEPS}) |
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set_target_properties(${the_target} PROPERTIES |
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DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}" |
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ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH} |
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RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH} |
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INSTALL_NAME_DIR lib |
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OUTPUT_NAME ${the_target}) |
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|
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if(ENABLE_SOLUTION_FOLDERS) |
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set_target_properties(${the_target} PROPERTIES FOLDER "applications") |
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endif() |
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install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main) |
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@ -0,0 +1,118 @@ |
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#include <cstdio> |
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#include <cstring> |
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#include <string> |
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using std::string; |
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|
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#include <vector> |
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using std::vector; |
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|
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#include <fstream> |
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using std::ifstream; |
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using std::getline; |
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|
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#include <sstream> |
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using std::stringstream; |
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|
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#include <iostream> |
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using std::cerr; |
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using std::endl; |
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#include <opencv2/core.hpp> |
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using cv::Rect; |
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using cv::Size; |
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#include <opencv2/highgui.hpp> |
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using cv::imread; |
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#include <opencv2/core/utility.hpp> |
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using cv::CommandLineParser; |
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using cv::FileStorage; |
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#include <opencv2/xobjdetect.hpp> |
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using cv::xobjdetect::ICFDetectorParams; |
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using cv::xobjdetect::ICFDetector; |
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using cv::xobjdetect::WaldBoost; |
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using cv::xobjdetect::WaldBoostParams; |
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using cv::Mat; |
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static bool read_model_size(const char *str, int *rows, int *cols) |
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{ |
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int pos = 0; |
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if( sscanf(str, "%dx%d%n", rows, cols, &pos) != 2 || str[pos] != '\0' || |
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*rows <= 0 || *cols <= 0) |
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{ |
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return false; |
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} |
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return true; |
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} |
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|
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int main(int argc, char *argv[]) |
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{ |
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const string keys = |
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"{help | | print this message}" |
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"{pos_path | pos | path to training object samples}" |
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"{bg_path | bg | path to background images}" |
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"{bg_per_image | 5 | number of windows to sample per bg image}" |
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"{feature_count | 10000 | number of features to generate}" |
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"{weak_count | 100 | number of weak classifiers in cascade}" |
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"{model_size | 40x40 | model size in pixels}" |
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"{model_filename | model.xml | filename for saving model}" |
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; |
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|
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CommandLineParser parser(argc, argv, keys); |
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parser.about("FCW trainer"); |
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|
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if( parser.has("help") || argc == 1) |
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{ |
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parser.printMessage(); |
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return 0; |
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} |
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string pos_path = parser.get<string>("pos_path"); |
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string bg_path = parser.get<string>("bg_path"); |
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string model_filename = parser.get<string>("model_filename"); |
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|
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ICFDetectorParams params; |
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params.feature_count = parser.get<int>("feature_count"); |
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params.weak_count = parser.get<int>("weak_count"); |
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params.bg_per_image = parser.get<int>("bg_per_image"); |
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|
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string model_size = parser.get<string>("model_size"); |
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if( !read_model_size(model_size.c_str(), ¶ms.model_n_rows, |
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¶ms.model_n_cols) ) |
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{ |
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cerr << "Error reading model size from `" << model_size << "`" << endl; |
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return 1; |
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} |
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|
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if( params.feature_count <= 0 ) |
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{ |
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cerr << "feature_count must be positive number" << endl; |
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return 1; |
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} |
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|
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if( params.weak_count <= 0 ) |
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{ |
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cerr << "weak_count must be positive number" << endl; |
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return 1; |
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} |
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|
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if( params.bg_per_image <= 0 ) |
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{ |
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cerr << "bg_per_image must be positive number" << endl; |
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return 1; |
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} |
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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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|
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ICFDetector detector; |
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detector.train(pos_path, bg_path, params); |
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FileStorage fs(model_filename, FileStorage::WRITE); |
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fs << "icfdetector"; |
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detector.write(fs); |
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fs.release(); |
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} |
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