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import sensor               # 导入传感器模块，用于摄像头初始化和图像采集
import time                 # 导入时间模块，用于延时和FPS计算
import math                 # 导入数学模块，用于数学计算
from machine import UART    # 从machine模块导入UART，用于串口通信

# 初始化UART串口通信，UART(1)表示使用UART1，波特率115200
uart = UART(1, 115200)

# 传感器初始化和配置
sensor.reset()                                   # 重置并初始化摄像头传感器
sensor.set_pixformat(sensor.GRAYSCALE)           # 设置像素格式为灰度
sensor.set_framesize(sensor.VGA)                 # 设置帧大小为VGA (640x480)
sensor.set_windowing((140, 200))                 # 设置窗口裁剪区域为宽140，高200
sensor.skip_frames(time=2000)                    # 跳过前2000毫秒的帧，让自动曝光和自动增益稳定

# 创建时钟对象，用于计算并跟踪FPS
clock = time.clock()  # Tracks FPS.

# 图像中心坐标（基于窗口大小）
CENTER_X = 140 / 2
CENTER_Y = 200 // 2

# 实际场景中，窗口对应的真实物理尺寸（单位：毫米）
FRAME_WIDTH_MM = 175
FRAME_HIGHT_MM = 266

# 不同测距标定参数（示例）
# DISTANCE_MM_1 = 1100
# FRAME_WIDTH_PIXEL_1 = 104
DISTANCE_MM_2 = 1400                # 第二组标定：相机到A4纸的距离（毫米）
# FRAME_WIDTH_PIXEL_2 = 80
FRAME_HEIGHT_PIXEL_2 = 111         # 第二组标定：A4纸在图像中高度对应的像素值
# DISTANCE_MM_3 = 1800
# FRAME_WIDTH_PIXEL_3 = 64


def find_center_min_blob(blobs):
    """
    在候选blob列表中找到最靠近图像中心且面积最小的blob
    :param blobs: blob对象列表
    :return: 最优的blob对象或None
    """
    blob = None                     # 初始化结果为None
    min_area = 100000               # 设定一个较大的初始最小面积阈值
    for b in blobs:
        # 过滤：只保留中心偏移总和小于50像素的blob
        if abs(b.cx() - CENTER_X) + abs(b.cy() - CENTER_Y) > 50:
            print("nonononoonon1")
            continue
        # 如果当前blob面积大于min_area，则跳过
        if b.area() > min_area:
            continue
        # 更新最优blob和最小面积
        blob = b
        min_area = b.area()
    return blob


def find_center_max_blob(blobs):
    """
    在候选blob列表中找到最靠近图像中心且面积最大的blob
    :param blobs: blob对象列表
    :return: 最优的blob对象或None
    """
    blob = None                  # 初始化结果为None
    max_area = 0                 # 初始化最大面积阈值为0
    for b in blobs:
        # 过滤：只保留中心偏移总和小于50像素的blob
        if abs(b.cx() - CENTER_X) + abs(b.cy() - CENTER_Y) > 50:
            continue
        # 如果当前blob面积小于max_area，则跳过
        if b.area() < max_area:
            continue
        # 更新最优blob和最大面积
        blob = b
        max_area = b.area()
    return blob

# 主循环，不断获取图像并处理
while True:
    clock.tick()                  # 更新FPS计时
    img = sensor.snapshot()      # 捕获一帧图像

    # 寻找标定框（高亮区域）：灰度值范围150-256
    frames = img.find_blobs([(150, 256)])
    # 在标定框中找到最中心且面积最小的blob
    frame_blob = find_center_min_blob(frames)
    if not frame_blob:
        print("NO FRAME")        # 若未检测到标定框，跳过本帧
        continue

    # 根据标定参数计算与A4纸的距离（毫米）
    distance = DISTANCE_MM_2 * FRAME_HEIGHT_PIXEL_2 / frame_blob.h()

    # 定义A4纸内部ROI区域，缩小边缘5像素以排除框线
    frame_roi = (
        frame_blob.x() + 5,
        frame_blob.y() + 5,
        frame_blob.w() - 10,
        frame_blob.h() - 10
    )
    # 检查ROI尺寸有效性
    if frame_roi[2] <= 0 or frame_roi[3] <= 0:
        print("ROI ERROR")
        continue
    print(frame_roi)

    # 在ROI内寻找目标物（灰度0-80）
    objs = img.find_blobs([(0, 80)], roi=frame_roi)
    # 选取最中心且面积最小的目标blob
    obj_blob = find_center_min_blob(objs)
    if not obj_blob:
        print("NO OBJS")      # 若未检测到目标物，跳过本帧
        continue

    # 打印检测到的角点列表，用于后续三角形去重
    print(obj_blob.corners())
    corners = []
    # 去除过近的重复角点
    for i in range(len(obj_blob.corners())):
        flag = 0
        for j in range(i + 1, len(obj_blob.corners())):
            # 计算两点距离，小于15像素认为重复
            if math.sqrt((obj_blob.corners()[i][0] - obj_blob.corners()[j][0])**2
                         + (obj_blob.corners()[i][1] - obj_blob.corners()[j][1])**2) < 15:
                flag = 1
        if flag == 0:
            corners.append(obj_blob.corners()[i])
    print(corners)

    # 根据density（填充比）判断形状，并计算物体边长或直径（毫米）
    if 0.9 < obj_blob.density():
        # 高填充比，近似正方形
        print("正方形")
        # 另一种计算方法：周长映射
        obj_w_mm = math.sqrt((obj_blob.pixels()) / frame_blob.h()**2 * FRAME_HIGHT_MM**2)
    elif 0.6 < obj_blob.density():
        # 中等填充比，近似圆形
        print("圆形")
        obj_w_mm = obj_blob.h() / frame_blob.h() * FRAME_HIGHT_MM
    elif 0.4 < obj_blob.density():
        # 低填充比，可能三角形或正方形
        if len(corners) == 4:
            # 四个角点，仍视为正方形
            print("正方形")
            obj_w_mm = math.sqrt((obj_blob.pixels()) / frame_blob.h()**2 * FRAME_HIGHT_MM**2)
        else:
            # 三角形：基于像素面积映射，并考虑等边三角形公式
            print("三角形")
            obj_w_mm = math.sqrt((obj_blob.pixels() + 5) / frame_blob.h()**2
                                 * FRAME_HIGHT_MM**2 * 4 / math.sqrt(3))
    else:
        # 填充比过低，无法识别形状
        print("无法识别到形状")
        obj_w_mm = 0

    # 在图像上绘制结果文字和检测框
    img.draw_string(10, 10, "length:" + str(obj_w_mm) + "mm")   # 显示物体尺寸
    img.draw_string(10, 20, "distance:" + str(distance) + "mm") # 显示距离
    # 通过UART串口输出结果到外部设备（单位：cm）
    uart.write(f"D:{distance/10}cm,X:{obj_w_mm/10}cm\r\n".encode())
    # 绘制检测到的A4纸框和目标物的外接矩形
    img.draw_rectangle(frame_blob.rect())
    img.draw_rectangle(obj_blob.rect())

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\documentclass{article}
\usepackage{tikz}
\usetikzlibrary{shapes.geometric, arrows.meta, positioning}

\tikzset{
    startstop/.style={rectangle, rounded corners, minimum width=3cm, minimum height=1cm,text centered, draw=black, fill=white},
    process/.style={rectangle, minimum width=3cm, minimum height=1cm, text centered, draw=black, fill=white},
    decision/.style={diamond, minimum width=3cm, minimum height=1cm, text centered, draw=black, fill=white},
    arrow/.style={thick,->,>=stealth},
    io/.style={trapezium, trapezium left angle=70, trapezium right angle=110, minimum width=3cm, minimum height=1cm, text centered, draw=black, fill=white}
}

\begin{document}

\begin{tikzpicture}[node distance=2cm]

    \node (start) [startstop] {系统上电};
    \node (init) [process, below of=start] {各模块初始化};
    \node (rtc) [process, below of=init] {主控配置RTC唤醒};
    \node (decide) [decision, below of=rtc, yshift=-1cm] {系统待机？};
    \node (sleep) [process, right of=decide, xshift=3cm] {主控进入STOP模式};
    \node (cam_sleep) [process, right of=sleep, xshift=3cm] {摄像头休眠};
    \node (lcd_off) [process, right of=cam_sleep, xshift=3cm] {LCD关闭背光};
    \node (ina_off) [process, right of=lcd_off, xshift=3cm] {INA226关断模式};
    \node (wait) [io, right of=ina_off, xshift=3cm] {等待唤醒};

    \node (measure) [process, below of=decide, yshift=-1cm] {执行测量任务};
    \node (cam_work) [process, right of=measure, xshift=3cm] {摄像头工作：降帧率/分辨率};
    \node (ina_sample) [process, right of=cam_work, xshift=3cm] {INA226间隔采样};
    \node (data_process) [process, right of=ina_sample, xshift=3cm] {数据处理};
    \node (lcd_show) [process, right of=data_process, xshift=3cm] {LCD显示数据};
    \node (lcd_dim) [io, right of=lcd_show, xshift=3cm] {降低LCD亮度};

    \draw [arrow] (start) -- (init);
    \draw [arrow] (init) -- (rtc);
    \draw [arrow] (rtc) -- (decide);
    \draw [arrow] (decide) -- node[anchor=south] {是} (sleep);
    \draw [arrow] (sleep) -- (cam_sleep);
    \draw [arrow] (cam_sleep) -- (lcd_off);
    \draw [arrow] (lcd_off) -- (ina_off);
    \draw [arrow] (ina_off) -- (wait);
    \draw [arrow] (wait) |- node[anchor=north] {RTC定时/按键} (decide);

    \draw [arrow] (decide) -- node[anchor=east] {否} (measure);
    \draw [arrow] (measure) -- (cam_work);
    \draw [arrow] (cam_work) -- (ina_sample);
    \draw [arrow] (ina_sample) -- (data_process);
    \draw [arrow] (data_process) -- (lcd_show);
    \draw [arrow] (lcd_show) -- (lcd_dim);
    \draw [arrow] (lcd_dim) |- (decide);

\end{tikzpicture}

\end{document}