import sensor, image, time
from pyb import LED
import ustruct
from pyb import UART
from pyb import Pin
import pyb
# 初始化UART
uart = UART(3, 115200, timeout_char=200)
uart.init(115200, bits=8, parity=None, stop=1)
# 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_exposure(False, exposure_us=35000)
clock = time.clock()
# 初始化引脚和LED
pin1 = Pin('P1', Pin.IN, Pin.PULL_UP)
led = pyb.LED(3)
def sending_data(x1, y1, x2, y2, x3, y3, x4, y4, r1, r2, g1, g2):
# 打包数据并发送
data = ustruct.pack("<bbhhhhhhhhhhhhb",
0xa3, 0xb3,
int(x1), int(y1),
int(x2), int(y2),
int(x3), int(y3),
int(x4), int(y4),
int(r1), int(r2),
int(g1), int(g2),
0xc3)
uart.write(data)
def keys():
# 按键检测函数（根据实际需求实现）
pass
# 计算两条直线的交点（线段范围内）
def line_intersection(line1, line2):
# line1: 由两点组成的元组 ((x1,y1), (x2,y2))
# line2: 由两点组成的元组 ((x3,y3), (x4,y4))
(x1, y1), (x2, y2) = line1
(x3, y3), (x4, y4) = line2
# 计算分母（避免除以零）
denom = (x1 - x2) * (y3 - y4) - (y1 - y2) * (x3 - x4)
if denom == 0:
return None # 平行线，无交点
# 计算分子
t_num = (x1 - x3) * (y3 - y4) - (y1 - y3) * (x3 - x4)
u_num = -((x1 - x2) * (y1 - y3) - (y1 - y2) * (x1 - x3))
t = t_num / denom
u = u_num / denom
# 检查交点是否在线段范围内
if 0 <= t <= 1 and 0 <= u <= 1:
x = int(x1 + t * (x2 - x1))
y = int(y1 + t * (y2 - y1))
return (x, y)
else:
return None # 交点在线段外
# 红色和绿色阈值
red_threshold = [(99, 100, -7, 50, -60, 32)]
green_threshold = [(52, 100, -19, -128, -128, 127), (0, 100, -128, -24, -128, 127)]
while True:
clock.tick()
img = sensor.snapshot()#.lens_corr(strength=1.0, zoom=1.1)
img.gaussian(1, unsharp=True) # 高斯滤波增强图像
# 查找矩形
rects = img.find_rects(threshold=30000, ROI=(114, 68, 102, 100))
led.on() # 打开LED指示正在运行
max_area = 0
max_rect = None
# 查找最大矩形
for rect in rects:
area = rect.w() * rect.h()
if area > max_area:
max_area = area
max_rect = rect
if max_rect:
# 获取矩形角点
corners = max_rect.corners()
x1, y1 = corners[0]
x2, y2 = corners[1]
x3, y3 = corners[2]
x4, y4 = corners[3]
# 绘制原始角点（不同大小的圆）
img.draw_circle(x1, y1, 5, color=(0, 25, 0)) # 绿色小圆
img.draw_circle(x2, y2, 10, color=(0, 25, 0)) # 绿色中圆
img.draw_circle(x3, y3, 15, color=(0, 25, 0)) # 绿色大圆
img.draw_circle(x4, y4, 20, color=(0, 25, 0)) # 绿色最大圆
# 绘制矩形边框（蓝色线）
img.draw_line(x1, y1, x2, y2, color=(0, 0, 255)) # 上边 - 蓝色
img.draw_line(x2, y2, x3, y3, color=(0, 0, 255)) # 右边 - 蓝色
img.draw_line(x3, y3, x4, y4, color=(0, 0, 255)) # 底边 - 蓝色
img.draw_line(x4, y4, x1, y1, color=(0, 0, 255)) # 左边 - 蓝色
# ====== 每条边六等分（5个等分点）======
division_points = [] # 存储所有等分点（4条边，每条边5个点）
# 计算每条边的六等分点（5个点）
for i in range(4):
start = corners[i]
end = corners[(i + 1) % 4]
# 计算当前边的5个等分点
points = []
for j in range(1, 6): # j从1到5，对应5个等分点
ratio = j / 6.0 # 等分比例
x = int(start[0] + ratio * (end[0] - start[0]))
y = int(start[1] + ratio * (end[1] - start[1]))
points.append((x, y))
# 将1/3和2/3位置的点（即j=2和j=4）改为绿色，其余为黄色
if j == 2 or j == 4: # 1/3和2/3位置
img.draw_circle(x, y, 3, color=(0, 255, 0)) # 绿色圆点
else:
img.draw_circle(x, y, 3, color=(255, 255, 0)) # 黄色圆点
division_points.append(points) # 将当前边的点加入列表
# 打印所有等分点坐标（调试用）
print("六等分点坐标:")
for i, points in enumerate(division_points):
for j, point in enumerate(points):
print(f"边{i+1} 点{j+1}: ({point[0]}, {point[1]})")
# ====== 按规则连接等分点并计算黄色连线交点 ======
# 存储黄色连线（用于计算交点）
yellow_lines = []
for i in range(5): # 每个边有5个点
# 判断是否是1/3和2/3位置的连线（i=1和i=3）
if i == 1 or i == 3: # 1/3和2/3位置的连线
line_color = (0, 255, 0) # 绿色连线
else:
line_color = (255, 255, 0) # 黄色连线
# 记录黄色连线的两个端点（用于后续计算交点）
line1 = (division_points[0][i], division_points[2][4-i])
line2 = (division_points[1][i], division_points[3][4-i])
yellow_lines.append(line1)
yellow_lines.append(line2)
# 第一条边(上边)第i点 -> 第三条边(底边)第(4-i)点
img.draw_line(
division_points[0][i][0], division_points[0][i][1],
division_points[2][4-i][0], division_points[2][4-i][1],
color=line_color
)
# 第二条边(右边)第i点 -> 第四条边(左边)第(4-i)点
img.draw_line(
division_points[1][i][0], division_points[1][i][1],
division_points[3][4-i][0], division_points[3][4-i][1],
color=line_color
)
# 计算黄色连线之间的交点并标记
print("黄色连线交点坐标:")
# 遍历所有黄色连线，计算两两之间的交点
for i in range(len(yellow_lines)):
for j in range(i + 1, len(yellow_lines)):
line_a = yellow_lines[i]
line_b = yellow_lines[j]
intersection = line_intersection(line_a, line_b)
if intersection:
x, y = intersection
# 用红色圆圈标记交点
img.draw_circle(x, y, 1, color=(255, 0, 0), thickness=2)
print(f"交点 {i+1}-{j+1}: ({x}, {y})")
print("角点坐标:", x1, y1, x2, y2, x3, y3, x4, y4)
else:
# 未找到矩形时清零坐标
x1 = y1 = x2 = y2 = x3 = y3 = x4 = y4 = 0
# 红色斑点检测
red = img.find_blobs(red_threshold)
if red:
r = red[0]
img.draw_cross(r.cx(), r.cy(), color=(10, 10, 10)) # 绘制十字标记
r1 = r.cx()
r2 = r.cy()
else:
r1 = r2 = 0
# 绿色斑点检测
gree = img.find_blobs(green_threshold)
if gree:
g = gree[0]
img.draw_cross(g.cx(), g.cy(), color=(255, 0, 0)) # 绘制红色十字标记
g1 = g.cx()
g2 = g.cy()
else:
g1 = g2 = 0
# 发送所有数据
x1 = 154
y1 =145
sending_data(x1, y1, x2, y2, x3, y3, x4, y4, r1, r2, g1, g2)
注释黄线绿线，黄圈绿圈，给我完整代码
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本文介绍了如何使用jsplumb库解决ER图在不同浏览器窗口大小下不自适应的问题，通过监听窗口调整事件并调用repaintEverything方法实现图形的动态调整。同时提醒读者注意设置container的position样式。
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