foreword
(1) Many students have completed the first three questions based on my last blog, congratulations. Many students got stuck on the fourth question.
(2) I said that the code of OpenART mini is feasible. But they will not be ported to OpenMV, and again I will post the code after porting.
(3)Tucao, I do not understand. Why are so many people unable to be transplanted? Isn't this a matter of minutes? (wry smile)
Identify the rectangular frame and the corresponding corner points
(1) A strange error will appear on line 40 of this place, saying that corner is not defined. But it was clearly defined earlier by calling corner = r.corners().
(2) Then I wrote a sentence of corner = 0 in front, and the error message disappeared. This bug is very strange. I hope you pay attention
from machine import Pin
import sensor, image, time
import pyb
#import seekfree, pyb
# 初始化TFT180屏幕
#lcd = seekfree.LCD180(3)
# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 设置图像色彩格式为RGB565格式
sensor.set_framesize(sensor.QQVGA) # 设置图像大小为160*120
sensor.set_auto_whitebal(True) # 设置自动白平衡
sensor.set_brightness(3000) # 设置亮度为3000
sensor.skip_frames(time = 20) # 跳过帧
clock = time.clock()
corner = 0
while(True):
clock.tick()
img = sensor.snapshot()
# -----矩形框部分-----
# 在图像中寻找矩形
for r in img.find_rects(threshold = 10000):
# 判断矩形边长是否符合要求
if r.w() > 20 and r.h() > 20:
# 在屏幕上框出矩形
img.draw_rectangle(r.rect(), color = (255, 0, 0), scale = 4)
# 获取矩形角点位置
corner = r.corners()
# 在屏幕上圈出矩形角点
img.draw_circle(corner[0][0], corner[0][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[1][0], corner[1][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[2][0], corner[2][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[3][0], corner[3][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
# 打印四个角点坐标, 角点1的数组是corner[0], 坐标就是(corner[0][0],corner[0][1])
# 角点检测输出的角点排序每次不一定一致，矩形左上的角点有可能是corner0,1,2,3其中一个
corner1_str = f"corner1 = ({
corner[0][0]},{
corner[0][1]})"
corner2_str = f"corner2 = ({
corner[1][0]},{
corner[1][1]})"
corner3_str = f"corner3 = ({
corner[2][0]},{
corner[2][1]})"
corner4_str = f"corner4 = ({
corner[3][0]},{
corner[3][1]})"
print(corner1_str + "\n" + corner2_str + "\n" + corner3_str + "\n" + corner4_str)
# 显示到屏幕上，此部分会降低帧率
#lcd.show_image(img, 160, 120, 0, 0, zoom=0) #屏幕显示
# 打印帧率
#print(clock.fps())
Tracking Laser Lights
from machine import Pin
import sensor, image, time
import pyb
#import seekfree, pyb
# 初始化激光灯控制引脚P0，并置为高电平
laser_light=Pin("P0", Pin.OUT)
laser_light.value(1)
# 初始化TFT180屏幕
#lcd = seekfree.LCD180(3)
# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 设置图像色彩格式为RGB565格式
sensor.set_framesize(sensor.QQVGA) # 设置图像大小为160*120
sensor.set_auto_whitebal(True) # 设置自动白平衡
sensor.set_brightness(3000) # 设置亮度为3000
sensor.skip_frames(time = 20) # 跳过帧
clock = time.clock()
while(True):
clock.tick()
img = sensor.snapshot()
# -----跟踪激光部分-----
# 设置激光颜色阈值
red_td = [(56, 100, 45, 127, -128, 127)] # 这里要改
# 根据阈值找到色块
for b in img.find_blobs(red_td,pixels_threshold=2, area_threshold=15, merge=True,invert = 0):
# 在屏幕上画出色块
img.draw_rectangle(b.rect(), color = (0, 255, 0), scale = 2, thickness = 2)
# 打印激光色块的中心位置
# 使用b.x()获取色块矩形左上角X坐标
# 使用b.y()获取色块矩形左上角Y坐标
# 使用b.w()获取色块矩形宽度
# 使用b.h()获取色块矩形高度
# 矩形中心坐标为（x + w/2，y + h/2)
print(f"rect = {
b.x() + b.w()/2},{
b.y() + b.h()/2}")
break
# 显示到屏幕上，此部分会降低帧率
#lcd.show_image(img, 160, 120, 0, 0, zoom=0) #屏幕显示
# 打印帧率
#print(clock.fps())
Identify the rectangular frame and corresponding corner points and track the laser light
from machine import Pin
import sensor, image, time
#import seekfree, pyb
import pyb
# 初始化激光灯控制引脚，并置为高电平
laser_light=Pin("P9", Pin.OUT)
laser_light.value(1)
# 初始化TFT180屏幕
#lcd = seekfree.LCD180(3)
# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 设置图像色彩格式为RGB565格式
sensor.set_framesize(sensor.QQVGA) # 设置图像大小为160*120
sensor.set_auto_whitebal(True) # 设置自动白平衡
sensor.set_brightness(3000) # 设置亮度为3000
sensor.skip_frames(time = 20) # 跳过帧
clock = time.clock()
while(True):
clock.tick()
img = sensor.snapshot()
# -----矩形框部分-----
# 在图像中寻找矩形
for r in img.find_rects(threshold = 10000):
# 判断矩形边长是否符合要求
if r.w() > 20 and r.h() > 20:
# 在屏幕上框出矩形
img.draw_rectangle(r.rect(), color = (255, 0, 0), scale = 4)
# 获取矩形角点位置
corner = r.corners()
# 在屏幕上圈出矩形角点
img.draw_circle(corner[0][0], corner[0][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[1][0], corner[1][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[2][0], corner[2][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
img.draw_circle(corner[3][0], corner[3][1], 5, color = (0, 0, 255), thickness = 2, fill = False)
# 角点坐标打印详见OpenART mini识别矩形框以及对应角点文件
# -----跟踪激光部分-----
# 设置激光颜色阈值
red_td = [(56, 100, 45, 127, -128, 127)]
# 根据阈值找到色块
for b in img.find_blobs(red_td,pixels_threshold=2, area_threshold=15, merge=True,invert = 0):
# 在屏幕上画出色块
img.draw_rectangle(b.rect(), color = (0, 255, 0), scale = 2, thickness = 2)
break
# 坐标打印详见OpenART mini跟踪激光灯文件
# 显示到屏幕上，此部分会降低帧率
#lcd.show_image(img, 160, 120, 0, 0, zoom=0) #屏幕显示
# 打印帧率
print(clock.fps())