y4oi 发布的帖子

import sensor
import image
import time
import math

# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time=2000)

clock = time.clock()

# 检测黄色的颜色阈值
yellow_threshold = (35, 90, -20, 60, 40, 100)

# 插值函数，用于计算每个格子的角点
def interpolate(p1, p2, factor):
    return (p1[0] + (p2[0] - p1[0]) * factor, p1[1] + (p2[1] - p1[1]) * factor)

find_blobs = True

# 主循环
while True:
    clock.tick()
    img = sensor.snapshot().lens_corr(strength=1.0, zoom=1.0)

    if find_blobs:
        # 使用颜色阈值来识别黄色区域
        yellow_blobs = img.find_blobs([yellow_threshold], pixels_threshold=3000, area_threshold=3000, merge=True)

        max_area = 0
        max_rect = None

        # 遍历所有黄色区域
        for blob in yellow_blobs:
            # 在黄色区域内寻找矩形
            rects = img.find_rects(roi=blob.rect(), threshold=5000)

            for rect in rects:
                area = rect.w() * rect.h()
                aspect_ratio = rect.w() / rect.h()

                # 判断面积和长宽比是否符合条件
                if 0.8 < aspect_ratio < 1.2 and area > max_area and 50 < rect.w() < 100 and 50 < rect.h() < 100:
                    max_area = area
                    max_rect = rect

        # 如果找到符合条件的最大矩形
        if max_rect:
            corners = max_rect.corners()
            angle = -math.degrees(math.atan2(corners[1][1] - corners[0][1], corners[1][0] - corners[0][0]))

            if -45 < angle < 45:
                print("矩形旋转角度:", angle)

            # 绘制矩形的四个角点和边框
            for corner in corners:
                img.draw_circle(corner[0], corner[1], 5, color=(255, 0, 0), thickness=2, fill=False)
            for i in range(len(corners)):
                start_point = corners[i]
                end_point = corners[(i + 1) % 4]
                img.draw_line(start_point[0], start_point[1], end_point[0], end_point[1], color=(255, 0, 0))

            # 在棋盘上添加编号
            num = 9
            for row in range(3):
                for col in range(3):
                    # 计算每个格子的四个顶点的插值
                    top_left = interpolate(interpolate(corners[0], corners[3], row / 3.0), interpolate(corners[1], corners[2], row / 3.0), 1 - col / 3.0)
                    top_right = interpolate(interpolate(corners[0], corners[3], row / 3.0), interpolate(corners[1], corners[2], row / 3.0), 1 - (col + 1) / 3.0)
                    bottom_left = interpolate(interpolate(corners[0], corners[3], (row + 1) / 3.0), interpolate(corners[1], corners[2], (row + 1) / 3.0), 1 - col / 3.0)
                    bottom_right = interpolate(interpolate(corners[0], corners[3], (row + 1) / 3.0), interpolate(corners[1], corners[2], (row + 1) / 3.0), 1 - (col + 1) / 3.0)

                    # 计算格子的中心坐标
                    center_x = int((top_left[0] + bottom_right[0]) / 2)
                    center_y = int((top_left[1] + bottom_right[1]) / 2)

                    # 在每个格子的中心位置绘制编号
                    img.draw_string(center_x - 10, center_y - 10, str(num), color=(255, 0, 0), scale=2)
                    num -= 1

import sensor
import image
import time
import math

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

# 设置颜色阈值，以下是一个黄色的示例
yellow_threshold = (30, 100, -10, 50, -30, 50)  # H: 30-100, S: 10-50, V: 30-50

# 创建一个时钟对象以计算FPS
clock = time.clock()

def draw_rotated_rect(img, center, angle, width, height, color=(255, 0, 0)):
    """ 绘制旋转矩形 """
    # 计算矩形四个角的坐标
    half_width = width / 2
    half_height = height / 2

    # 旋转矩形的四个角
    points = [
        (-half_width, -half_height),
        (half_width, -half_height),
        (half_width, half_height),
        (-half_width, half_height)
    ]

    # 进行旋转
    rotated_points = []
    for point in points:
        x = point[0] * math.cos(angle) - point[1] * math.sin(angle)
        y = point[0] * math.sin(angle) + point[1] * math.cos(angle)
        rotated_points.append((x + center[0], y + center[1]))

    # 绘制旋转后的矩形
    img.draw_line(int(rotated_points[0][0]), int(rotated_points[0][1]), int(rotated_points[1][0]), int(rotated_points[1][1]), color=color)
    img.draw_line(int(rotated_points[1][0]), int(rotated_points[1][1]), int(rotated_points[2][0]), int(rotated_points[2][1]), color=color)
    img.draw_line(int(rotated_points[2][0]), int(rotated_points[2][1]), int(rotated_points[3][0]), int(rotated_points[3][1]), color=color)
    img.draw_line(int(rotated_points[3][0]), int(rotated_points[3][1]), int(rotated_points[0][0]), int(rotated_points[0][1]), color=color)

while True:
    clock.tick()
    img = sensor.snapshot()

    # 查找黄色色块
    blobs = img.find_blobs([yellow_threshold], pixels_threshold=200, area_threshold=200, merge=True)

    # 检测到的小框的角度和中心点
    centers = []
    angles = []
    rects = []

    # 遍历找到的色块
    for blob in blobs:
        # 过滤掉小的噪声
        if blob.area() > 100:
            # 获取色块的矩形框
            rect = blob.rect()
            rects.append(rect)
            # 判断是否为正方形
            if abs(rect[2] - rect[3]) < 10:  # 允许宽高差异小于10像素
                # 计算中心点和旋转角度
                center = (blob.cx(), blob.cy())
                angle = math.atan2(rect[3], rect[2])  # 计算旋转角度
                centers.append(center)
                angles.append(angle)

                # 绘制九宫格小框
                img.draw_rectangle(rect)

    # 如果检测到了九个小框
    if len(centers) == 9:
        # 计算九个小框的外接矩形
        min_x = min([rect[0] for rect in rects])
        min_y = min([rect[1] for rect in rects])
        max_x = max([rect[0] + rect[2] for rect in rects])
        max_y = max([rect[1] + rect[3] for rect in rects])

        # 计算大矩形的中心点和角度
        center_x = (min_x + max_x) // 2
        center_y = (min_y + max_y) // 2
        avg_angle = sum(angles) / len(angles)

        # 计算大矩形的宽度和高度
        width = max_x - min_x
        height = max_y - min_y

        # 绘制旋转后的大矩形
        draw_rotated_rect(img, (center_x, center_y), avg_angle, width, height, color=(0, 255, 0))

    print("FPS: {}".format(clock.fps()))

请在这里粘贴代码