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Conclusão sobre as Previsões e Apostas

Analisando todas essas informações detalhadas sobre as equipes participantes neste emocionante confronto entre o Mali e seu adversário amanhã, fica claro que há várias opções estratégicas para quem deseja fazer apostas informadas. Avaliar cuidadosamente as estatísticas recentes, entender as táticas possíveis e considerar fatores externos são passos essenciais para maximizar suas chances de sucesso nas apostas esportivas. Esperamos que essas informações ajudem você a tomar decisões mais informadas sobre suas aposta<|repo_name|>kunlin-xiao/human-skeleton-tracking<|file_sep|>/src/BodyPart.cpp #include "BodyPart.h" namespace human_skeleton_tracking { BodyPart::BodyPart() { } BodyPart::BodyPart(int id) { this->id = id; } BodyPart::BodyPart(int id, cv::Point3f position, float confidence) { this->id = id; this->position = position; this->confidence = confidence; } void BodyPart::set_id(int id) { this->id = id; } void BodyPart::set_position(cv::Point3f position) { this->position = position; } void BodyPart::set_confidence(float confidence) { this->confidence = confidence; } int BodyPart::get_id() { return this->id; } cv::Point3f BodyPart::get_position() { return this->position; } float BodyPart::get_confidence() { return this->confidence; } } // namespace human_skeleton_tracking <|repo_name|>kunlin-xiao/human-skeleton-tracking<|file_sep cadek<|file_sep |============================================================================== Human Skeleton Tracking Library ============================================================================== This is an OpenCV library that can track the human skeleton in images and videos. The skeleton model has the following parts: * head * neck * shoulder_left * shoulder_right * elbow_left * elbow_right * wrist_left * wrist_right * hip_left * hip_right * knee_left * knee_right * ankle_left * ankle_right The tracking method is based on OpenPose [1]. [1]: https://github.com/CMU-Perceptual-Computing-Lab/openpose You can see some results in the `examples` folder. The skeleton tracking can be used in the following ways: 1) Track the skeletons in an image or video file. cpp // Import necessary headers. #include "HumanSkeletonTracker.h" #include "opencv2/highgui/highgui.hpp" int main(int argc, char *argv[]) { // Read image or video file. cv::Mat img_or_video_file = cv::imread("path/to/image.jpg", cv::IMREAD_COLOR); // Create an instance of HumanSkeletonTracker. human_skeleton_tracking::HumanSkeletonTracker human_skeleton_tracker; // Track skeletons in image or video file. std::vector* skeletons = human_skeleton_tracker.track(img_or_video_file); // Draw skeletons on image or video file. human_skeleton_tracker.draw(*skeletons, img_or_video_file, cv::Scalar(0x00ff00)); // Show image or video file. cv::imshow("Image or Video File", img_or_video_file); cv::waitKey(0); } 2) Track the skeletons from camera. cpp // Import necessary headers. #include "HumanSkeletonTracker.h" #include "opencv2/highgui/highgui.hpp" int main(int argc, char *argv[]) { // Get camera input stream. cv::VideoCapture cap(0); // Create an instance of HumanSkeletonTracker. human_skeleton_tracking::HumanSkeletonTracker human_skeleton_tracker; while (true) { // Get frame from camera. cv::Mat frame; cap >> frame; // Track skeletons in frame. std::vector* skeletons = human_skeleton_tracker.track(frame); // Draw skeletons on frame. human_skeleton_tracker.draw(*skeletons, frame, cv::Scalar(0x00ff00)); // Show frame. cv::imshow("Camera", frame); cv::waitKey(1); if (cv::waitKey(30) >= 0) break; } } 3) Track the skeletons from OpenCV windows. cpp // Import necessary headers. #include "HumanSkeletonTracker.h" #include "opencv2/highgui/highgui.hpp" int main(int argc, char *argv[]) { // Create an instance of HumanSkeletonTracker. human_skeleton_tracking::HumanSkeletonTracker human_skeleton_tracker; while (true) { // Show window with title 'Camera'. cvNamedWindow("Camera", CV_WINDOW_AUTOSIZE); // Track skeletons from window with title 'Camera'. std::vector* skeletons = human_skeleton_tracker.track("Camera"); // Draw skeletons on window with title 'Camera'. human_skeleton_tracker.draw(*skeletons, cvGetWindowHandle("Camera"), cvScalar(0x00ff00)); if (cvWaitKey(30) >= 0) break; } } 4) Track the skeletons from OpenCV windows asynchronously. cpp // Import necessary headers. #include "HumanSkeletonTracker.h" #include "opencv2/highgui/highgui.hpp" int main(int argc, char *argv[]) { // Create an instance of HumanSkeletonTracker. human_skeleton_tracking::HumanSkeletonTracker human_skeleton_tracker; while (true) { // Show window with title 'Camera'. cvNamedWindow("Camera", CV_WINDOW_AUTOSIZE); // Track skeletons asynchronously from window with title 'Camera'. std::vector* skeletons = human_skeleton_tracker.track_async("Camera"); // Draw skeletons on window with title 'Camera'. human_skeleton_tracker.draw(*skeletons, cvGetWindowHandle("Camera"), cvScalar(0x00ff00)); if (cvWaitKey(30) >= 0) break; } } 5) Track the skeletons from OpenCV windows asynchronously with callback function. cpp // Import necessary headers. #include "HumanSkeletonTracker.h" #include "opencv2/highgui/highgui.hpp" void callback( const std::vector& skeletons, cvWindow& window, const cvScalar& color) { for (const auto& skeleton : skeletons) skeleton.draw(window.getNativeHandle(), color); } int main(int argc, char *argv[]) { // Create an instance of HumanSkeletonTracker. human_skeleton_tracking::HumanSkeletonTracker human_skeleton_tracker; while (true) { cvNamedWindow("Camera", CV_WINDOW_AUTOSIZE); human_skeleton_tracker.track_async("Camera", callback); if (cvWaitKey(30) >= 0) break; } } <|repo_name|>kunlin-xiao/human-skeleton-tracking<|file_sep-- vi: set ft=lua : project = "human-skeleton-tracking" project_description = [[A library for tracking the human skeleton in images and videos]] project_url = "https://github.com/kunlin-xiao/human-skeleton-tracking" project_license = [[MIT]] dependencies = { { name = "OpenCV", kind = "system" }, { name = "OpenMP", kind = "system" }, } includedirs = { project .. "/include" } files { project .. "/src/*.cpp" } defines { "__OPENCV__", "__OPENCV__LIB__" } links { "opencv_world300" } libdirs { "$(OPENCV_DIR)/lib" } configurations { "Debug*" } defines { "_DEBUG" } flags { "Symbols" } configurations { "Release*" } defines { "NDEBUG" } flags { "OptimizeSpeed" } configuration { "linux-*" } buildoptions { "-std=c++11", "-fopenmp", "-Wno-sign-compare", "-Wno-unused-parameter", "-Wno-deprecated-declarations" } linkoptions { "-fopenmp" } configuration { "macosx-*" } buildoptions { "-std=c++11", "-fopenmp", "-Wno-sign-compare", "-Wno-unused-parameter", "-Wno-deprecated-declarations" } linkoptions { "-fopenmp -framework Accelerate -framework vecLib -mmacosx-version-min=10.7 -stdlib=libc++" } configuration {} <|file_sep cabal-version: >=1.18 name: human-skeletal-tracking-openmp version: .1.0.0 license: MIT license-file: LICENSE.md author: Kunlin Xiao extra-source-files: README.md library hs-source-dirs: c_src/ c_src/include/ src/ src/include/ exposed-modules: HumanSkeletalTracking.OpenMP build-depends: base >=4 && <=5, vector-carray ==0.1.* default-language: Haskell2010 cc-options: -std=c++11 -fopenmp -Wno-sign-compare -Wno-unused-parameter -Wno-deprecated-declarations ld-options: -fopenmp <|repo_name|>kunlin-xiao/human-skeleton-tracking<|file_sepncpp-pch.h -o $@ $(CXXFLAGS) $(CPPFLAGS) $@ : $< $(OBJDIR)/%.o : $(SRCDIR)/%.cpp $(CPPH) mkdir -p $(OBJDIR)/$(dir $@) g++ $< -I$(SRCDIR) -I$(SRCDIR)/include $(