参考上海交通大学代码进行修改

Catalyst-MDVS2/src/MindVisionMain.cpp

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+#include <cstdlib>
+#include <iostream>
+#include <string>
+#include <vector>
+#include <chrono>
+#include <thread>
+#include <memory>
+#include <unistd.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"
+
+// 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)
+        int ballistic_offset_x = -static_cast<int>(ballistic_point->x - img_center.x);
+        if ( abs(ballistic_offset_x) > 320){
+            ballistic_offset_x = ( ballistic_offset_x / abs( ballistic_offset_x ) ) * 320 ;
+        }
+        int ballistic_offset_y = -static_cast<int>(img_center.y - ballistic_point->y);
+        if ( abs(ballistic_offset_y) > 180 ) {
+            ballistic_offset_y = ( ballistic_offset_x / abs( ballistic_offset_x ) ) * 180 ;
+        }
+
+        // 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_x) << " " << std::to_string(ballistic_offset_y) << "*\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);
+
+            // 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;
+}