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