import cv2 import numpy as np import tkinter as tk from tkinter import colorchooser, simpledialog, Scale, HORIZONTAL, messagebox from threading import Thread # 颜色的HSV阈值 color_hsv_ranges = { 'blue': {'lower': np.array([80, 170, 192], dtype=np.uint8), 'upper': np.array([120, 255, 255], dtype=np.uint8)}, 'green': {'lower': np.array([25, 50, 147], dtype=np.uint8), 'upper': np.array([55, 255, 255], dtype=np.uint8)}, 'red': {'lower': np.array([0, 112, 194] , dtype=np.uint8), 'upper': np.array([13, 255, 255], dtype=np.uint8)}, 'custom': {'lower': np.array([0, 0, 0], dtype=np.uint8), 'upper': np.array([180, 255, 255], dtype=np.uint8)} } # 初始化选择的颜色 selected_color = 'green' #获取初始颜色HSV阈值 lower_hsv, upper_hsv = (color_hsv_ranges[selected_color]['lower'], color_hsv_ranges[selected_color]['upper']) # 全局变量 running = False kf = None cap = None root = None stop_thread = False def initialize_kalman_filter(): """初始化卡尔曼滤波器""" global kf kf = cv2.KalmanFilter(4, 2) kf.measurementMatrix = np.array([[1, 0, 0, 0], [0, 1, 0, 0]], np.float32) kf.transitionMatrix = np.array([[1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32) kf.processNoiseCov = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32) * 0.03 # 用于初始化卡尔曼滤波器的变量 initial_measurement = None #初始化摄像头 def initialize_camera(): global cap cap = cv2.VideoCapture(0) def choose_color(): global selected_color # 显示颜色选择对话框 color_options = list(color_hsv_ranges.keys()) selected_color = simpledialog.askstring("选择颜色", "输入颜色 (blue, green, red, custom):", initialvalue=selected_color, parent=root) # 检查颜色选择是否有效，更新阈值 if selected_color in color_options: update_color_threshold(selected_color) else: messagebox.showerror("错误", "颜色选择无效") def update_color_threshold(color_name): """更新颜色阈值""" global lower_hsv, upper_hsv, selected_color # 根据选择的颜色更新颜色阈值 selected_color = color_name # 更新selected_color lower_hsv = color_hsv_ranges[color_name]['lower'] upper_hsv = color_hsv_ranges[color_name]['upper'] def rgb_to_hsv(rgba): """将RGB颜色转换为HSV颜色""" rgb = rgba[:3] # 忽略alpha通道 hsv = cv2.cvtColor(np.uint8([[rgb]]), cv2.COLOR_RGB2HSV)[0][0] return hsv def choose_custom_color(): color_code = colorchooser.askcolor(title="选择自定义颜色") if color_code[0] is not None: hsv_color = rgb_to_hsv(color_code[0]) # 计算HSV的下限和上限 lower = np.array([hsv_color[0] - 35, hsv_color[1] * 0.5, hsv_color[2] * 0.65]) upper = np.array([hsv_color[0] + 10, hsv_color[1] * 1.2, hsv_color[2] * 1.2]) # 确保HSV值在有效范围内 lower = np.clip(lower, 0, 180) upper = np.clip(upper, 0, 255) # 更新自定义颜色的HSV阈值 update_custom_hsv(lower, upper) # 更新自定义颜色的HSV阈值 def update_custom_hsv(lower, upper): global color_hsv_ranges color_hsv_ranges['custom']['lower'] = lower.astype(np.uint8) color_hsv_ranges['custom']['upper'] = upper.astype(np.uint8) update_color_threshold('custom') def exit_app(): global running, cap, stop_thread running = False stop_thread = True root.quit() cap.release() cv2.destroyAllWindows() def initialize_gui(): """初始化GUI界面""" global root root = tk.Tk() root.geometry("200x600") root.title("颜色追踪") # 开始/停止摄像头按钮 start_button = tk.Button(root, text="开始/停止", command=start_camera) start_button.pack() # 颜色选择按钮 choose_color_button = tk.Button(root, text="选择颜色", command=choose_color) choose_color_button.pack() # 自定义颜色按钮 custom_color_button = tk.Button(root, text="自定义颜色", command=choose_custom_color) custom_color_button.pack() # 退出按钮 exit_button = tk.Button(root, text="退出", command=exit_app) exit_button.pack() # 自定义颜色HSV滑块 def set_custom_hsv(lower_h, lower_s, lower_v, upper_h, upper_s, upper_v): update_custom_hsv( np.array([lower_h, lower_s, lower_v]), np.array([upper_h, upper_s, upper_v]) ) # 自定义颜色HSV滑块 lower_h_scale = Scale(root, from_=0, to=180, orient=HORIZONTAL, label="色调 Min", command=lambda v: set_custom_hsv(v, lower_s_scale.get(), lower_v_scale.get(), upper_h_scale.get(), upper_s_scale.get(), upper_v_scale.get())) lower_h_scale.pack() lower_s_scale = Scale(root, from_=0, to=255, orient=HORIZONTAL, label="饱和度 Min", command=lambda v: set_custom_hsv(lower_h_scale.get(), v, lower_v_scale.get(), upper_h_scale.get(), upper_s_scale.get(), upper_v_scale.get())) lower_s_scale.pack() lower_v_scale = Scale(root, from_=0, to=255, orient=HORIZONTAL, label="亮度 Min", command=lambda v: set_custom_hsv(lower_h_scale.get(), lower_s_scale.get(), v, upper_h_scale.get(), upper_s_scale.get(), upper_v_scale.get())) lower_v_scale.pack() upper_h_scale = Scale(root, from_=0, to=180, orient=HORIZONTAL, label="色调 Max", command=lambda v: set_custom_hsv(lower_h_scale.get(), lower_s_scale.get(), lower_v_scale.get(), v, upper_s_scale.get(), upper_v_scale.get())) upper_h_scale.pack() upper_s_scale = Scale(root, from_=0, to=255, orient=HORIZONTAL, label="饱和度 Max", command=lambda v: set_custom_hsv(lower_h_scale.get(), lower_s_scale.get(), lower_v_scale.get(), upper_h_scale.get(), v, upper_v_scale.get())) upper_s_scale.pack() upper_v_scale = Scale(root, from_=0, to=255, orient=HORIZONTAL, label="亮度 Max", command=lambda v: set_custom_hsv(lower_h_scale.get(), lower_s_scale.get(), lower_v_scale.get(), upper_h_scale.get(), upper_s_scale.get(), v)) upper_v_scale.pack() # 初始化滑块值 lower_h_scale.set(color_hsv_ranges['custom']['lower'][0]) lower_s_scale.set(color_hsv_ranges['custom']['lower'][1]) lower_v_scale.set(color_hsv_ranges['custom']['lower'][2]) upper_h_scale.set(color_hsv_ranges['custom']['upper'][0]) upper_s_scale.set(color_hsv_ranges['custom']['upper'][1]) upper_v_scale.set(color_hsv_ranges['custom']['upper'][2]) def start_camera(): """开始或停止摄像头处理""" global running if not running: running = True thread = Thread(target=camera_thread) thread.start() else: running = False def camera_thread(): """摄像头处理线程函数""" global running, initial_measurement, lower_hsv, upper_hsv, stop_thread while running and not stop_thread: ret, frame = cap.read() if not ret: messagebox.showerror("Error", "Failed to read frame from camera.") running = False break # 将BGR图像转换为HSV hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, lower_hsv, upper_hsv) # 应用开运算（先腐蚀后膨胀）以去除噪声 kernel_opening = np.ones((5, 5), np.uint8) mask_opened = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel_opening) # 应用闭运算（先膨胀后腐蚀）以填充孔洞 kernel_closing = np.ones((5, 5), np.uint8) mask_closed = cv2.morphologyEx(mask_opened, cv2.MORPH_CLOSE, kernel_closing) # 使用闭合后的掩模找到轮廓 contours, _ = cv2.findContours(mask_closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 遍历轮廓，画出边界框 for contour in contours: if cv2.contourArea(contour) > 300: x, y, w, h = cv2.boundingRect(contour) cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2) # 初始化卡尔曼滤波器的测量值 if initial_measurement is None: initial_measurement = np.array([[x], [y]], np.float32) kf.statePost = initial_measurement else: # 更新卡尔曼滤波器 measurement = np.array([[x], [y]], np.float32) kf.correct(measurement) prediction = kf.predict() cv2.rectangle(frame, (int(prediction[0]), int(prediction[1])), (int(prediction[0] + w), int(prediction[1] + h)), (255, 0, 0), 2) cv2.imshow('Frame', frame) cv2.imshow('Mask', mask) if cv2.waitKey(1) & 0xFF == ord('q'): running = False cv2.destroyAllWindows() def main(): """主函数，程序入口""" initialize_kalman_filter() initialize_camera() initialize_gui() root.mainloop() if __name__ == "__main__": main()