Catalyst-MDVS/src/MindVisionMain.cpp

#include <cstdlib>
#include <iostream>
#include <string>
#include <vector>
#include <chrono>
#include <thread>
#include <memory>
#include <unistd.h>
#include <math.h>
#include <opencv2/opencv.hpp>
#include <opencv2/tracking.hpp>

#include "config.h"
#include "MindVisionCamera.h"  // 使用MindVision相机
#include "ImagePreprocessor.h"
#include "ArmorDetector.h"
#include "KalmanFilter.h"
#include "Visualizer.h"
#include "BallisticPredictor.h"
#include "TTLCommunicator.h"
#include "PidController.h"

// Global PID controllers for pitch and yaw
PidController pitch_pid(0.1f, 0.01f, 0.05f); // Default PID values for pitch
PidController yaw_pid(0.1f, 0.01f, 0.05f);   // Default PID values for yaw

// Global pointers to PID controllers to be accessed by trackbar callbacks
PidController* g_pitch_pid = &pitch_pid;
PidController* g_yaw_pid = &yaw_pid;

// Callback functions for trackbars
void on_pitch_kp_trackbar(int pos, void*) {
    g_pitch_pid->setKp(pos / 100.0f);
}

void on_pitch_ki_trackbar(int pos, void*) {
    g_pitch_pid->setKi(pos / 1000.0f);
}

void on_pitch_kd_trackbar(int pos, void*) {
    g_pitch_pid->setKd(pos / 100.0f);
}

void on_yaw_kp_trackbar(int pos, void*) {
    g_yaw_pid->setKp(pos / 100.0f);
}

void on_yaw_ki_trackbar(int pos, void*) {
    g_yaw_pid->setKi(pos / 1000.0f);
}

void on_yaw_kd_trackbar(int pos, void*) {
    g_yaw_pid->setKd(pos / 100.0f);
}

// Function to output control data to TTL device (with enable control)
void output_control_data(const cv::Point2f* ballistic_point,
                        const std::string& target_color,
                        TTLCommunicator* ttl_communicator,
                        const cv::Point2f& img_center,
                        bool use_ttl) {
    // Only send data when TTL is enabled and has valid target
    if (use_ttl && ballistic_point != nullptr) {
        std::ostringstream send_str;

        // Calculate offset (based on actual image center)
        float raw_offset_x = -(ballistic_point->x - img_center.x); // yaw error
        float raw_offset_y = -(img_center.y - ballistic_point->y); // pitch error

        // Calculate time delta (assuming we have access to time)
        static auto last_time = std::chrono::high_resolution_clock::now();
        auto current_time = std::chrono::high_resolution_clock::now();
        float dt = std::chrono::duration<float>(current_time - last_time).count();
        if (dt < 0.001f) dt = 0.01f; // Minimum dt to avoid division by zero
        last_time = current_time;

        // Apply PID control to the pitch (vertical) component
        float pid_pitch_output = pitch_pid.update(0.0f, raw_offset_y, dt); // Setpoint is 0, error is raw_offset_y

        // Apply PID control to the yaw (horizontal) component
        float pid_yaw_output = yaw_pid.update(0.0f, raw_offset_x, dt); // Setpoint is 0, error is raw_offset_x

        // Convert PID outputs to the expected format
        // The PID output might be large, so we might need to scale it
        int ballistic_offset_yaw = static_cast<int>(pid_yaw_output);
        int ballistic_offset_pitch = static_cast<int>(pid_pitch_output);

        // Apply same limits as before
        if (abs(ballistic_offset_yaw) > 320) {
            ballistic_offset_yaw = (ballistic_offset_yaw / abs(ballistic_offset_yaw)) * 220; // Keep the scale factor
        }
        if (abs(ballistic_offset_pitch) > 180) {
            // Use the same scale factor as before
            ballistic_offset_pitch = (ballistic_offset_pitch / abs(ballistic_offset_pitch)) * 180 * 1.9;
        }

        // Color simplification mapping
        std::string simplified_color = target_color;
        if (target_color == "red") simplified_color = "r";
        else if (target_color == "blue") simplified_color = "b";

        // Construct send string (original format)
        send_str << "#s " << simplified_color << " " << std::to_string(ballistic_offset_yaw) << " " << std::to_string(ballistic_offset_pitch) << "*\n";

        // Send data
        if (ttl_communicator != nullptr) {
            ttl_communicator->send_data(send_str.str());
        }else{
            std::cerr << "Error: TTLCommunicator is a null pointer!" << std::endl;
        }
    }
}

void set_camera_resolution(MindVisionCamera& camera, int width, int height) {
    // The resolution is set during camera initialization in MindVision
    // We need to implement a method in MindVisionCamera to change resolution
    // For now, we'll just log the intended change
   if (camera.set_resolution(width, height)){
        std::cout << "Successfully set camera resolution to: " << width << "x" << height << std::endl;
   } else {
        std::cerr << "Failed to set camera resolution to: " << width << "x" << height << std::endl;
   }
}

int main(int /*argc*/, char* /*argv*/[]) {
    static int Numbe = 0;
    std::string target_color = "red";
    int cam_id = 0;
    cv::Size default_resolution(640, 480); // Changed to 640x480 for consistency with SJTU project
    bool use_ttl = false; // Set to false to disable TTL communication


    if (Numbe == 0) {
        // 执行 shell 命令（注意安全风险！）
        std::system("sudo chmod 777 /dev/tty*");
        Numbe++;
    }

    // Define optional resolution list (adjust based on camera support)
    std::vector<cv::Size> resolutions = {
        cv::Size(320, 240),   // Low resolution, high frame rate
        cv::Size(640, 480),   // Standard resolution
        cv::Size(1280, 720),  // HD resolution
        cv::Size(1920, 1080)  // Full HD resolution
    };

    // Find the index of default resolution
    int res_index = 1; // Default to index 1 (640x480)
    for (size_t i = 0; i < resolutions.size(); i++) {
        if (resolutions[i] == default_resolution) {
            res_index = static_cast<int>(i);
            break;
        }
    }

    // Initialize TTL communication (only when enabled)
    TTLCommunicator* ttl = nullptr;
    if (use_ttl) {
        // On Linux, the port would typically be /dev/ttyUSB0, /dev/ttyACM0, etc.
        ttl = new TTLCommunicator("/dev/ttyUSB0", TTL_BAUDRATE);
        if (ttl != nullptr) {
            if (!ttl->connect()) {
                std::cout << "Warning: Cannot establish TTL connection, will continue running but not send data" << std::endl;
            }
        } else {
            std::cout << "Error: Failed to create TTL communicator instance" << std::endl;
        }
    } else {
        std::cout << "TTL communication disabled" << std::endl;
    }

    // Initialize visual processing modules with MindVision camera
    MindVisionCamera camera(cam_id, target_color);
    if (!camera.is_opened) {
        std::cerr << "Cannot open MindVision camera!" << std::endl;
        return -1;
    }

    // Initialize ballistic predictor (adjustable bullet speed, e.g., 16m/s)
    BallisticPredictor ballistic_predictor(16.0f);
    // Record target speed (obtained from Kalman filter)
    cv::Point2f target_speed(0.0f, 0.0f);

    // Set initial resolution
    set_camera_resolution(camera, resolutions[res_index].width, resolutions[res_index].height);
    std::cout << "Initial camera resolution: " << resolutions[res_index].width << "x" << resolutions[res_index].height << std::endl;

    ImagePreprocessor preprocessor;
    ArmorDetector detector;
    KalmanFilter kalman_tracker;
    Visualizer visualizer;

    // Initialize KCF tracker
    cv::Ptr<cv::Tracker> tracker = cv::TrackerKCF::create();
    bool is_tracking = false;
    cv::Rect2d tracking_roi;
    int tracking_frame_count = 0;
    const int MAX_TRACKING_FRAMES = 100; // Maximum frames to track before returning to search

    int frame_counter = 0; // Counter to control output frequency
    int max_consecutive_predicts = 20; // Maximum consecutive prediction times
    int consecutive_predicts = 0; // Current consecutive prediction count

    cv::Mat frame;
    try {
        while (true) {
            // 使用新的颜色过滤方法同时获取图像和原始掩码

            cv::Mat raw_mask;
            if (!camera.read_frame_with_color_filter(frame, raw_mask, target_color)) {
                std::cout << "Cannot read from MindVision camera, exiting!，HERERER" << std::endl;
                break;
            }

            // Get actual image size and calculate center
            cv::Point2f img_center(frame.cols / 2.0f, frame.rows / 2.0f);

            // 使用OpenCV进行形态学处理
            cv::Mat mask;
            preprocessor.apply_morphology(raw_mask, mask);

            // 生成彩色图像（仅显示目标颜色）
            cv::Mat color_only_frame;
            frame.copyTo(color_only_frame, raw_mask);

            // Initialize tracking center
            cv::Point2f* tracking_center = nullptr;
            std::unique_ptr<cv::Point2f> tracking_point = nullptr;

            if (is_tracking) {
                // Update tracker
                bool success = tracker->update(frame, tracking_roi);
                if (success && tracking_roi.area() > 0) {
                    // Calculate center of tracked ROI
                    tracking_point = std::make_unique<cv::Point2f>(
                        tracking_roi.x + tracking_roi.width / 2.0f,
                        tracking_roi.y + tracking_roi.height / 2.0f
                    );
                    tracking_center = tracking_point.get();
                    tracking_frame_count++;

                    // If tracking for too long or detection is available, search for armor again
                    if (tracking_frame_count > MAX_TRACKING_FRAMES) {
                        is_tracking = false;
                        tracking_frame_count = 0;
                    }
                } else {
                    // Tracking failed, return to detection mode
                    is_tracking = false;
                    tracking_frame_count = 0;
                }
            }

            // Armor plate detection - only when not tracking or need to verify tracking
            std::vector<LightBar> valid_light_bars;
            std::vector<ArmorPlate> armor_plates;

            if (!is_tracking || tracking_frame_count % 10 == 0) { // Detect every 10 frames when tracking
                detector.detect(mask, target_color, valid_light_bars, armor_plates);
            }

            // Kalman filter tracking (modified part: get target speed)
            cv::Point2f* detection_center = nullptr;
            if (!armor_plates.empty()) {
                detection_center = &(armor_plates[0].center);
            }

            // Use smart pointer for safer memory management
            std::unique_ptr<cv::Point2f> predicted_center = nullptr;

            // Priority: detection -> tracking -> Kalman prediction
            if (detection_center != nullptr) {
                // Has detection result: update Kalman filter, reset consecutive prediction count
                kalman_tracker.update(*detection_center);
                predicted_center = std::make_unique<cv::Point2f>(kalman_tracker.predict());

                // Start tracking if successfully detected
                if (!is_tracking && !armor_plates.empty()) {
                    cv::Rect2d armor_rect = cv::boundingRect(std::vector<cv::Point2f>{
                        armor_plates[0].corners_2d[0],
                        armor_plates[0].corners_2d[1],
                        armor_plates[0].corners_2d[2],
                        armor_plates[0].corners_2d[3]
                    });
                    // Expand the bounding box slightly for better tracking
                    cv::Rect2d expanded_rect = cv::Rect2d(
                        armor_rect.x - armor_rect.width * 0.1,
                        armor_rect.y - armor_rect.height * 0.1,
                        armor_rect.width * 1.2,
                        armor_rect.height * 1.2
                    );
                    // Ensure the rectangle is within frame bounds
                    expanded_rect = expanded_rect & cv::Rect2d(0, 0, frame.cols, frame.rows);

                    tracker = cv::TrackerKCF::create(); // Create new tracker instance
                    tracker->init(frame, expanded_rect);
                    tracking_roi = expanded_rect;
                    is_tracking = true;
                    tracking_frame_count = 0;
                }

                consecutive_predicts = 0;
            } else if (is_tracking && tracking_center != nullptr) {
                // Use tracking result
                kalman_tracker.update(*tracking_center);
                predicted_center = std::make_unique<cv::Point2f>(kalman_tracker.predict());
                consecutive_predicts = 0;
            } else {
                // No detection or tracking result: only use Kalman prediction, limit consecutive predictions
                consecutive_predicts++;
                if (consecutive_predicts < max_consecutive_predicts) {
                    cv::Point2f temp_pred = kalman_tracker.predict();
                    if (temp_pred.x != 0 || temp_pred.y != 0) { // Check if prediction is valid
                        predicted_center = std::make_unique<cv::Point2f>(temp_pred);
                    }
                } else {
                    predicted_center = nullptr;
                    target_speed = cv::Point2f(0.0f, 0.0f);
                }
            }

            // Determine display center
            cv::Point2f* display_center = detection_center; // Give priority to detection results
            if (display_center == nullptr && is_tracking && tracking_center != nullptr) {
                display_center = tracking_center;
            }
            if (display_center == nullptr && predicted_center != nullptr) {
                display_center = predicted_center.get();
            }
            bool is_predicted = (display_center != nullptr) && (detection_center == nullptr && (!is_tracking || tracking_center == nullptr));

            // Calculate ballistic prediction point
            cv::Point2f* ballistic_point = ballistic_predictor.predict_ballistic_point(
                predicted_center.get(), img_center, target_speed
            );

            auto current_time = std::chrono::high_resolution_clock::now();

            // Visualization
            visualizer.draw_light_bars(frame, valid_light_bars, target_color);
            if (!armor_plates.empty()) {
                visualizer.draw_armor_plate(frame, armor_plates[0]);
            }
            // Draw tracking rectangle if tracking
            if (is_tracking) {
                cv::rectangle(frame, tracking_roi, cv::Scalar(0, 255, 0), 2);
            }
            visualizer.draw_offset_text(frame, display_center, target_color, is_predicted);
            visualizer.draw_ballistic_point(frame, ballistic_point);

            // Output control data to TTL (passing use_ttl to control whether to send)
            // Now sending on every frame for smoother control
            output_control_data(display_center, target_color, ttl, img_center, use_ttl);

            // Create trackbars for PID parameter tuning
            static bool initialized_trackbars = false;
            if (!initialized_trackbars) {
                cv::namedWindow("PID Tuning", cv::WINDOW_AUTOSIZE);

                // Create trackbars for pitch PID parameters
                cv::createTrackbar("Pitch Kp", "PID Tuning", nullptr, 1000, on_pitch_kp_trackbar);
                cv::createTrackbar("Pitch Ki", "PID Tuning", nullptr, 1000, on_pitch_ki_trackbar);
                cv::createTrackbar("Pitch Kd", "PID Tuning", nullptr, 1000, on_pitch_kd_trackbar);

                // Create trackbars for yaw PID parameters
                cv::createTrackbar("Yaw Kp", "PID Tuning", nullptr, 1000, on_yaw_kp_trackbar);
                cv::createTrackbar("Yaw Ki", "PID Tuning", nullptr, 1000, on_yaw_ki_trackbar);
                cv::createTrackbar("Yaw Kd", "PID Tuning", nullptr, 1000, on_yaw_kd_trackbar);

                // Set initial positions
                cv::setTrackbarPos("Pitch Kp", "PID Tuning", static_cast<int>(pitch_pid.getKp() * 100));
                cv::setTrackbarPos("Pitch Ki", "PID Tuning", static_cast<int>(pitch_pid.getKi() * 1000));
                cv::setTrackbarPos("Pitch Kd", "PID Tuning", static_cast<int>(pitch_pid.getKd() * 100));
                cv::setTrackbarPos("Yaw Kp", "PID Tuning", static_cast<int>(yaw_pid.getKp() * 100));
                cv::setTrackbarPos("Yaw Ki", "PID Tuning", static_cast<int>(yaw_pid.getKi() * 1000));
                cv::setTrackbarPos("Yaw Kd", "PID Tuning", static_cast<int>(yaw_pid.getKd() * 100));

                initialized_trackbars = true;
            }

            // Update trackbar positions in case they were changed externally
            cv::setTrackbarPos("Pitch Kp", "PID Tuning", static_cast<int>(pitch_pid.getKp() * 100));
            cv::setTrackbarPos("Pitch Ki", "PID Tuning", static_cast<int>(pitch_pid.getKi() * 1000));
            cv::setTrackbarPos("Pitch Kd", "PID Tuning", static_cast<int>(pitch_pid.getKd() * 100));
            cv::setTrackbarPos("Yaw Kp", "PID Tuning", static_cast<int>(yaw_pid.getKp() * 100));
            cv::setTrackbarPos("Yaw Ki", "PID Tuning", static_cast<int>(yaw_pid.getKi() * 1000));
            cv::setTrackbarPos("Yaw Kd", "PID Tuning", static_cast<int>(yaw_pid.getKd() * 100));

            // Display windows
            cv::imshow("Armor Detection", frame);
            cv::imshow(target_color + " Mask", mask);
            cv::imshow(target_color + " Only", color_only_frame);

            // Exit on 'q' key press
            if (cv::waitKey(1) == 'q') {
                break;
            }

            frame_counter++;

            // Control max frame rate (100 FPS)
            auto end_time = std::chrono::high_resolution_clock::now();
            auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(end_time - current_time).count();
            if (elapsed < 10) { // 100 FPS = 10ms per frame
                std::this_thread::sleep_for(std::chrono::milliseconds(10 - elapsed));
            }

            // Smart pointers automatically handle memory cleanup
        }
    }
    catch (const std::exception& e) {
        std::cerr << "Error in main loop: " << e.what() << std::endl;
    }
    catch (...) {
        std::cerr << "Unknown error occurred in main loop" << std::endl;
    }

    // Cleanup
    try {
        camera.release();
    } catch (...) {
        std::cerr << "Error during camera release" << std::endl;
    }

    try {
        cv::destroyAllWindows();
    } catch (...) {
        std::cerr << "Error during window destruction" << std::endl;
    }

    // Only close TTL connection when enabled and initialized
    if (use_ttl && ttl != nullptr) {
        try {
            ttl->close();
        } catch (...) {
            std::cerr << "Error during TTL close" << std::endl;
        }
        delete ttl;
        ttl = nullptr;
    }

    return 0;
}