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original.py
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original.py
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#coding: UTF-8
#include "windows.h"
import cv2
import numpy as np
import time
from operator import itemgetter
import wiringpi
import sys
import pygame.mixer
#射影変換行列を計算するキャリブレーション用関数
def calibration(areas):
pts1 = np.float32([[135,65],[400,65],[135,330],[400,330]]) #areasと同じ順 (左上，右上，左下，右下)
#areasの格納が普通の配列じゃないので，配列に書き直す．
x0=areas[0][0][0][0]
y0=areas[0][0][0][1]
x1=areas[0][1][0][0]
y1=areas[0][1][0][1]
x2=areas[0][2][0][0]
y2=areas[0][2][0][1]
x3=areas[0][3][0][0]
y3=areas[0][3][0][1]
p0 = [x0,y0]
p1 = [x1,y1]
p2 = [x2,y2]
p3 = [x3,y3]
area = [p0,p1,p2,p3]
#areasの4つの座標を左上，右上，左下，右下の順で並び替える．台形の場合x座標の順で一意に決定
#np.float32リストに対してitemgetterは使えないらしい
area.sort(key=itemgetter(0))
#スケール変換変換
k = (pts1[3][0]-pts1[2][0])/(area[2][0]-area[1][0])
h = (area[1][1]-area[0][1])*k
delta = (area[1][0]-area[0][0])*k
x1 = pts1[2]+[-delta,-h]
x2 = pts1[3]+[delta,-h]
pts2 = np.float32([x1,x2,pts1[2],pts1[3]])
M = cv2.getPerspectiveTransform(pts1,pts2)
return M
#台形補正画像を生成する関数
def revision(M,img):
inv_M =np.linalg.inv(M)
dst = cv2.warpPerspective(img,inv_M,(0,800))
return dst
#ターゲット(黄色)の輪郭を取ってくる関数
def getTarget(image):
# Convert BGR to HSV and smooth
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
smooth=cv2.GaussianBlur(hsv,(15,15),0)
#黄色
lower_blue = np.array([25,100,85])
upper_blue = np.array([100,255,255])
# Threshold the HSV image to get only blue colors
mask = cv2.inRange(smooth, lower_blue, upper_blue)
# Bitwise-AND mask and original image(白黒画像の中で，白の部分だけ筒抜けになって映る)
res = cv2.bitwise_and(frame,frame, mask= mask)
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
areas = []
contours.sort(key=cv2.contourArea,reverse=True)
if contours:
cnt = contours[0]
epsilon = 0.08*cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,epsilon,True)
areas.append(approx)
else:
cnt = []
return areas,res,cnt,
#台形補正用にwebcameraから輪郭をとってくる．
def getBlue(frame):
# Convert BGR to HSV and smooth
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
smooth=cv2.GaussianBlur(hsv,(15,15),0)
# define range of blue color in HSV (第1引数を110〜130→90〜140に変更)
lower_blue = np.array([90,50,50])
upper_blue = np.array([140,255,255])
# Threshold the HSV image to get only blue colors
mask = cv2.inRange(smooth, lower_blue, upper_blue)
# Bitwise-AND mask and original image(白黒画像の中で，白の部分だけ筒抜けになって映る)
res = cv2.bitwise_and(frame,frame, mask= mask)
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
areas = []
contours.sort(key=cv2.contourArea,reverse=True)
if contours:
cnt = contours[0]
epsilon = 0.08*cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,epsilon,True)
areas.append(approx)
else:
cnt = []
return areas,res,cnt,
#輪郭の重心を計算
def center_of_image(image):
areas,_,_ = getTarget(image)
if areas:
try:
M = cv2.moments(areas[0])
x = int(M['m10']/M['m00'])
y = int(M['m01']/M['m00'])
except ZeroDivisionError:
print ("zerodivision")
else:
x=0
y=0
return x,y
#backをforeを中心から(x,y)移動させて重ね合わせる
def clip_image(x, y, back, fore):
h1, w1, _ = back.shape
h2, w2, _ = fore.shape
X = int((w1-w2)/2)
Y = int((h1-h2)/2)
if abs(x)< X and abs(y)<Y:
back[Y+y:Y+h2+y,X+x:X+w2+x] = fore
#+xではみ出す，
elif x >=X and abs(y)<Y:
back[Y+y:Y+h2+y,X+X:X+w2+X,] = fore
#-xではみ出す，
elif -x >=X and abs(y)<Y:
back[Y+y:Y+h2+y,0:w2] = fore
#+yではみ出す，
elif abs(x)<X and y>=Y:
back[Y+Y:Y+h2+Y,X+x:X+w2+x] = fore
#-yではみ出す，
elif abs(x)<X and -y>Y:
back[0:h2,X+x:X+w2+x] = fore
#+x，+yではみ出す，
elif x >=X and y>=Y:
back[Y+Y:Y+h2+Y,X+X:X+X+w2] = fore
#-x,+yではみ出す，
elif -x >=X and y>=Y:
back[Y+Y:Y+h2+Y,0:w2] = fore
#+x,+yではみ出す，
elif x >=X and y>=Y:
back[Y:Y+h2+Y,X+X:X+X+w2] = fore
#+x,-yではみ出す，
elif x >=X and -y>=Y:
back[0:h2,X+X:X+X+w2] = fore
"""
ここまで関数定義
"""
#無地
back1 = cv2.imread("back.png",1)
back2 = cv2.imread("back.png",1)
back3 = cv2.imread("back.png",1)
back4 = cv2.imread("back.png",1)
img_right1 = cv2.imread("right1.png",1)
img_right2 = cv2.imread("right2.png",1)
img_right3 = cv2.imread("right3.png",1)
img_right4 = cv2.imread("right4.png",1)
img_left1 = cv2.imread("left1.png",1)
img_left2 = cv2.imread("left2.png",1)
img_left3 = cv2.imread("left3.png",1)
img_left4 = cv2.imread("left4.png",1)
img_stop1 = cv2.imread("stop1.png",1)
img_stop2 = cv2.imread("stop2.png",1)
img_stop3 = cv2.imread("stop3.png",1)
img_rest1 = cv2.imread("rest1.png",1)
img_rest2 = cv2.imread("rest2.png",1)
calibration_img = cv2.imread("calibration.png",1)
cv2.namedWindow("img", cv2.WND_PROP_FULLSCREEN)
# cv2.namedWindow("img", cv2.WND_PROP_FULLSCREEN)
# cv2.setWindowProperty("img", cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
button_pin1 = 4 # 7番端子
button_pin2 = 17 # 11番端子
button_pin3 = 27 # 13番端子
button_pin4 = 22 # 15番端子
button_pin5 = 10 # 19番端子
# GPIO初期化
wiringpi.wiringPiSetupGpio()
# GPIOを出力モード（1）に設定
wiringpi.pinMode( button_pin1, 0 )
wiringpi.pinMode( button_pin2, 0 )
wiringpi.pinMode( button_pin3, 0 )
wiringpi.pinMode( button_pin4, 0 )
wiringpi.pinMode( button_pin5, 0 )
# 端子に何も接続されていない場合の状態を設定
# 3.3Vの場合には「2」（プルアップ）
# 0Vの場合は「1」と設定する（プルダウン）
wiringpi.pullUpDnControl( button_pin1, 2 )
wiringpi.pullUpDnControl( button_pin2, 2 )
wiringpi.pullUpDnControl( button_pin3, 2 )
wiringpi.pullUpDnControl( button_pin4, 2 )
wiringpi.pullUpDnControl( button_pin5, 2 )
#↓ラズパイ(opencv2)の方でやらないとなぜか動かない(PCはopencv3)
# cv2.namedWindow("img", cv2.WND_PROP_FULLSCREEN)
# cv2.setWindowProperty("img", cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
capture = cv2.VideoCapture(0)
count = 0
l = []
m = []
M = []
# isOpenedの代わりにTrueを使うと，frameがemptyのときエラーを吐く
while capture.isOpened():
ret, frame = capture.read()
if ret :
#とりあえず常に黄色の輪郭をとってくるようにする．
areas,res,_= getTarget(frame)
#キャリブレーションボタンが押された場合(右)3秒間，射影変換行列を計算
if wiringpi.digitalRead(button_pin1) == 0 :
#3秒間投影し，Mを計算
while True:
cv2.imshow('img',calibration_img)
cv2.waitKey(1)
time.sleep(0.6)
count =count+1
if count>5:
break
pts1 = np.float32([[135,65],[400,65],[135,330],[400,330]])
pts2 = np.float32([[105,45],[430,45],[135,330],[400,330]])
M = cv2.getPerspectiveTransform(pts1,pts2)
img_right1 = revision(M,img_right1)
img_right2 = revision(M,img_right2)
img_right3 = revision(M,img_right3)
img_right4 = revision(M,img_right4)
img_left1 = revision(M,img_left1)
img_left2 = revision(M,img_left2)
img_left3 = revision(M,img_left3)
img_left4 = revision(M,img_left4)
img_stop1 = revision(M,img_stop1)
img_stop2 = revision(M,img_stop2)
img_stop3 = revision(M,img_stop3)
img_rest1 = revision(M,img_rest1)
img_rest2 = revision(M,img_rest2)
pygame.mixer.init()
pygame.mixer.music.load('calibration_finished.mp3')
pygame.mixer.music.play(1) # ()内は再生回数 -1:ループ再生
print ("calibrating...")
#スイッチ2(右)が押された場合．
elif wiringpi.digitalRead(button_pin2) == 0:
print ("turnright")
#frameから輪郭をとる
cv2.imshow('img',img_right1)
cv2.waitKey(500)
cv2.imshow('img',img_right2)
cv2.waitKey(500)
cv2.imshow('img',img_right3)
cv2.waitKey(500)
cv2.imshow('img',img_right4)
cv2.waitKey(800)
#スイッチ3(左)が押された場合．
elif wiringpi.digitalRead(button_pin3) == 0:
print ("turnright")
#frameから輪郭をとる
cv2.imshow('img',img_left1)
cv2.waitKey(500)
cv2.imshow('img',img_left2)
cv2.waitKey(500)
cv2.imshow('img',img_left3)
cv2.waitKey(500)
cv2.imshow('img',img_left4)
cv2.waitKey(800)
#スイッチ4(stop)が押された場合．
elif wiringpi.digitalRead(button_pin4) == 0:
print ("stop")
#frameから輪郭をとる
cv2.imshow('img',img_stop1)
cv2.waitKey(500)
cv2.imshow('img',img_stop2)
cv2.waitKey(500)
cv2.imshow('img',back3)
cv2.waitKey(500)
#スイッチ5(rest)が押された場合．
elif wiringpi.digitalRead(button_pin5) == 0:
print ("rest")
#frameから輪郭をとる
cv2.imshow('img',img_rest1)
cv2.waitKey(200)
cv2.imshow('img',img_rest2)
cv2.waitKey(2000)
#スイッチOFFのとき．
else :
print ("switch off")
back = cv2.imread("back.png",1)
cv2.imshow('img',back)
#waitKeyの引数を0以下にするとキー入力する毎に画面がframeが更新する．
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()