写一个基于openmv摄像头识别红绿蓝三种色块，并用串口发送，并至少使用卡尔曼滤波的代码

以下是基于OpenMV摄像头识别红绿蓝三种色块并使用卡尔曼滤波的代码：

import sensor
import image
import time
import pyb
from kalman_filter import *

# 初始化串口
uart = pyb.UART(3, 9600, timeout_char=1000)

# 初始化卡尔曼滤波器
kf_red = KalmanFilter(1, 1)
kf_green = KalmanFilter(1, 1)
kf_blue = KalmanFilter(1, 1)

# 设置色块阈值
red_threshold = (30, 100, 15, 80, 15, 70)
green_threshold = (30, 100, -50, -10, -50, -10)
blue_threshold = (15, 50, -50, -10, 0, 30)

# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)

# 主循环
while(True):
    # 获取图像
    img = sensor.snapshot()
    # 识别红色色块
    blobs_red = img.find_blobs([red_threshold], pixels_threshold=200, area_threshold=200)
    if blobs_red:
        # 获取红色色块的中心点坐标
        x, y, w, h = blobs_red[0].rect()
        x_center = x + int(w / 2)
        y_center = y + int(h / 2)
        # 使用卡尔曼滤波器更新坐标
        x_center_filtered, y_center_filtered = kf_red.update([x_center, y_center])
        # 发送坐标到串口
        uart.write("red: X={0:d}, Y={1:d}\n".format(int(x_center_filtered), int(y_center_filtered)))
        # 在图像上标记红色色块
        img.draw_rectangle(blobs_red[0].rect())
        img.draw_cross(x_center_filtered, y_center_filtered)
    # 识别绿色色块
    blobs_green = img.find_blobs([green_threshold], pixels_threshold=200, area_threshold=200)
    if blobs_green:
        # 获取绿色色块的中心点坐标
        x, y, w, h = blobs_green[0].rect()
        x_center = x + int(w / 2)
        y_center = y + int(h / 2)
        # 使用卡尔曼滤波器更新坐标
        x_center_filtered, y_center_filtered = kf_green.update([x_center, y_center])
        # 发送坐标到串口
        uart.write("green: X={0:d}, Y={1:d}\n".format(int(x_center_filtered), int(y_center_filtered)))
        # 在图像上标记绿色色块
        img.draw_rectangle(blobs_green[0].rect())
        img.draw_cross(x_center_filtered, y_center_filtered)
    # 识别蓝色色块
    blobs_blue = img.find_blobs([blue_threshold], pixels_threshold=200, area_threshold=200)
    if blobs_blue:
        # 获取蓝色色块的中心点坐标
        x, y, w, h = blobs_blue[0].rect()
        x_center = x + int(w / 2)
        y_center = y + int(h / 2)
        # 使用卡尔曼滤波器更新坐标
        x_center_filtered, y_center_filtered = kf_blue.update([x_center, y_center])
        # 发送坐标到串口
        uart.write("blue: X={0:d}, Y={1:d}\n".format(int(x_center_filtered), int(y_center_filtered)))
        # 在图像上标记蓝色色块
        img.draw_rectangle(blobs_blue[0].rect())
        img.draw_cross(x_center_filtered, y_center_filtered)
    # 延时
    time.sleep(10)

其中，`kalman_filter.py`文件是卡尔曼滤波器的实现，如下所示：

class KalmanFilter:
    def __init__(self, n, m):
        self.A = array([[1, 0], [0, 1]])
        self.H = array([[1, 0], [0, 1]])
        self.Q = 0.01 * eye(n)
        self.R = 1 * eye(m)
        self.P = 0.1 * eye(2)
        self.x = zeros((2, 1))

    def update(self, z):
        # Prediction
        self.x = dot(self.A, self.x)
        self.P = dot(dot(self.A, self.P), self.A.T) + self.Q

        # Correction
        y = z - dot(self.H, self.x)
        S = dot(dot(self.H, self.P), self.H.T) + self.R
        K = dot(dot(self.P, self.H.T), inv(S))
        self.x = self.x + dot(K, y)
        self.P = dot((eye(2) - dot(K, self.H)), self.P)

        return self.x.ravel()