开始之前:

1. 识别标签输出相关数据

HUSKYLENS 2能识别出现在画面中的AprilTag标签,可以通过编程获取画面中检测到的标签相关数据。可以读取的标签数据有:指定标签的数据,包括标签ID、标签内容、标签宽度、标签高度以及标签中心点的X坐标位置和Y坐标位置等、检测到的标签总数。

示例程序如下。

#  -*- coding: UTF-8 -*-

# MindPlus
# Python
from unihiker import GUI
from pinpong.board import Board
from dfrobot_huskylensv2 import *


u_gui=GUI()
Board().begin()
huskylens = HuskylensV2_I2C()
huskylens.knock()
huskylens.switchAlgorithm(ALGORITHM_TAG_RECOGNITION)
line1=u_gui.draw_text(text="",x=0,y=0,font_size=18, color="#0000FF")
line2=u_gui.draw_text(text="",x=0,y=40,font_size=18, color="#0000FF")
line3=u_gui.draw_text(text="",x=0,y=80,font_size=18, color="#0000FF")
line4=u_gui.draw_text(text="",x=0,y=120,font_size=18, color="#0000FF")
while True:
    huskylens.getResult(ALGORITHM_TAG_RECOGNITION)
    if (huskylens.available(ALGORITHM_TAG_RECOGNITION)):
        line1.config(text=(str("标签总数:") + str((huskylens.getCachedResultNum(ALGORITHM_TAG_RECOGNITION)))))
        line2.config(text=(str("已学习的标签总数:") + str((huskylens.getCachedResultMaxID(ALGORITHM_TAG_RECOGNITION)))))
        line3.config(text=(str("靠近中心的标签ID:") + str((huskylens.getCachedCenterResult(ALGORITHM_TAG_RECOGNITION).ID if huskylens.getCachedCenterResult(ALGORITHM_TAG_RECOGNITION) else -1))))
        line4.config(text=(str("第一个标签ID:") + str((huskylens.getCachedResultByIndex(ALGORITHM_TAG_RECOGNITION, 1-1).ID if huskylens.getCachedResultByIndex(ALGORITHM_TAG_RECOGNITION, 1-1) else -1))))

在Mind+中点击运行程序,等待程序上传完成后。

将HUSKYLENS 2的摄像头对准画面中的标签可进行学习,如何学习标签详细操作请看:二哈识图 2 标签识别功能说明

将HUSKYLENS 2的摄像头对准标签码,观察K10屏幕显示的结果。

**运行结果:**如图所示,可输出检测到的标签码数量(无论是否该标签码已学习)、可输出指定的标签ID,未学习的标签码则为0。

Interface Diagram

2. 获取画面中指定标签的相关数据

HUSKYLENS 2识别标签后,可获取画面中指定标签的相关数据。例如,判断某个指定ID的标签是否在画面中、可获取画面中相同ID的标签数量,当画面中出现多个相同ID的标签时,可指定获取其中某个标签的相关参数,包括名称、内容、X/Y坐标、宽度、高度。

示例程序如下:

#  -*- coding: UTF-8 -*-

# MindPlus
# Python
from unihiker import GUI
from pinpong.board import Board
from dfrobot_huskylensv2 import *


u_gui=GUI()
Board().begin()
huskylens = HuskylensV2_I2C()
huskylens.knock()
huskylens.switchAlgorithm(ALGORITHM_TAG_RECOGNITION)
line1=u_gui.draw_text(text="",x=0,y=0,font_size=18, color="#0000FF")
line2=u_gui.draw_text(text="",x=0,y=40,font_size=18, color="#0000FF")
line3=u_gui.draw_text(text="",x=0,y=65,font_size=18, color="#0000FF")
line4=u_gui.draw_text(text="",x=0,y=105,font_size=18, color="#0000FF")
line5=u_gui.draw_text(text="",x=0,y=130,font_size=18, color="#0000FF")
while True:
    huskylens.getResult(ALGORITHM_TAG_RECOGNITION)
    if (huskylens.available(ALGORITHM_TAG_RECOGNITION)):
        if ((huskylens.getCachedResultByID(ALGORITHM_TAG_RECOGNITION, 0) is not None)):
            line1.config(text=(str("ID0标签总数:") + str((huskylens.getCachedResultNumByID(ALGORITHM_TAG_RECOGNITION, 0)))))
            line2.config(text="第一个ID0标签")
            line3.config(text=(str("的内容:") + str((huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 1-1).content if huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 1-1) else -1))))
            line4.config(text="第2个ID0标签")
            line5.config(text=(str("的坐标:") + str((str((huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 2-1).xCenter if huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 2-1) else -1)) + str((str(",") + str((huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 2-1).yCenter if huskylens.getCachedIndexResultByID(ALGORITHM_TAG_RECOGNITION, 0, 2-1) else -1))))))))

**运行结果:**如图所示,画面中有两个未学习的标签码(ID为0),第一个ID0标签是左边的,该标签的内容是48,第二个ID0标签是右边的,该标签的坐标是(505,263)。

Interface Diagram