#from camera import camera
from ultrasonic import ultrasonic
from infrared import infrared
from line_tracker import line_tracker
#import cv2
import time
address='192.168.0.101'
#cam = camera(address)
#cam.start()
inf = infrared(address)
inf.start()
ult = ultrasonic(address)
ult.start()
lt = line_tracker(address)
lt.start()
inf_t = time.time()
while True:
try:
t = time.time()
# if cam.image!=[]:
# cv2.imshow("image",cam.image)
# cv2.waitKey(1)
if t-inf_t>1:
print("infrared left,right: ",inf.left,inf.right)
print("ultrasonic: ",ult.measurement)
print("line_tracker: ",lt.data)
inf_t = t
def __init__(self):
self.sonic = ultrasonic()
print("Hello~Are you OK????")
GPIO.setwarnings(False)
GPIO.setmode(
GPIO.BCM
) #referring to pins by Boardcom SOC channel (i.e. not physical pin numbers)
# setup LCD
lcd = CharLCD(numbering_mode=GPIO.BCM,
pin_rs=26,
pin_e=19,
pins_data=[21, 20, 16, 12],
cols=16,
rows=2)
lcd.clear()
# setup ultrasonics
uL = US.ultrasonic(trig=8, echo=7)
uR = US.ultrasonic(trig=6, echo=5)
uB = US.ultrasonic(trig=27, echo=22)
# setup motors
mL = MC.motor(23, 18, 14) # enable, pin1, pin2
mR = MC.motor(4, 17, 3) # enable, pin1, pin2
# setup encoders
eL = EC.encoder(24, 25) #outA, out B
eR = EC.encoder(9, 11)
radius = 5 #in cm
distanceL = 0 # initialize distance travelled by left wheel
distanceR = 0 # initialize distance travelled by right wheel
#setup pulsecounts
from subprocess import call
# initialize all
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))
lastTime = 0
faceState = -1
# allow the camera to warmup
time.sleep(0.1)
ultrasonicInstance = ultrasonic(18, 16)
# capture frames from the camera
for frame in camera.capture_continuous(rawCapture,
format="bgr",
use_video_port=True):
# grab the raw NumPy array representing the image, then initialize the timestamp
# and occupied/unoccupied text
image = frame.array
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + w]
import RPi.GPIO as GPIO
from time import sleep
import ultrasonic as US
import numpy as np
# setup ultrasonics
uL = US.ultrasonic(8,7)
uR = US.ultrasonic(6,5)
uB = US.ultrasonic(27,22)
# initialize variables
max_dist=0
min_dist=100
tot_dist=0
for i in range(20):
dist = uL.measure()
max_dist = max(max_dist,dist)
min_dist = min(min_dist,dist)
tot_dist += dist
mean_dist = tot_dist/20
print("mean: "+str(mean_dist))
print("range: "+str((max_dist-min_dist)/2))
import ultrasonic
import accelerometer
import icamera
import time
import gsm
print '\n\n...................VEHICLE TRACKER..............\n\n\n'
##velocity,speed = ultrasonic.ultrasonic()
speed = ultrasonic.ultrasonic()
if (speed > 40):
print '\n\nRule Break : Out of speed\n\n'
##x,y,z=accelerometer. accelerometer()
stri = str(time.time()) + '.jpg'
no_plate = icamera.mycamera(stri)
#no_plate=' '
p = no_plate
gsm.gsm(p)
opt = raw_input('Do you want to search a particular vehicle? : (y/n)')
if opt == 'y':
no_plate_check = input('Enter vehicle no : ')
if no_plate == no_plate_check:
print 'Found'
else:
print 'Not found'
else:
print 'ok'
print '\n\nODD...EVEN\n\n'
if ((int)(no_plate)) % 2 == 0: