def __init__(self):
self.env = simpy.Environment()
self.db = database.data()
self.db.load_sql()
self.lines = {}
self.stores = {}
self.log = pd.DataFrame()
def __init__(self):
self.env = simpy.Environment()
self.db = database.data()
self.db.load_sql()
self.lines = {}
self.stores = {}
self.log = pd.DataFrame()
def results(request):
# On lance l'algorithme des mariages stables sur l'ensemble des ecoles et
# etudiants inscrits
d = data()
guyprefers = d.guyprefers
galprefers = d.galprefers
capacity = d.capacity
engaged, rejected = matchmaker(guyprefers, galprefers, capacity)
#On affiche le resultat et on transmet l'information a la partie HTML
print(engaged)
c = {'engaged': engaged,
'rejected': rejected,
}
return render_to_response(r'results.html', c)
def main():
# argument for input video/image/calibration
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to video file")
ap.add_argument("-i", "--image", help="Path to the image")
ap.add_argument("-c", "--calibration", help="image or video or camera")
args = vars(ap.parse_args())
if args.get("calibration", True):
imgOriginalScene = cv2.imread(args["calibration"])
if imgOriginalScene is None:
print("Please check again the path of image or argument !")
imgOriginalScene = imutils.resize(imgOriginalScene, width=640)
cal.calibration(imgOriginalScene)
return
if args.get("video", True):
camera = cv2.VideoCapture(args["video"])
if camera is None:
print(" Please check again the path of video or argument !")
loop = True
elif args.get("image", True):
#imgOriginalScene = cv2.imread(args["image"])
imgOriginalScene = cv2.imread("tes_plat_indo/B6703WJF.jpg")
if imgOriginalScene is None:
print(" Please check again the path of image or argument !")
loop = False
else:
#camera = cv2.VideoCapture("rtsp://*****:*****@192.168.0.159:554/PSIA/streaming/channels/101")
camera = cv2.VideoCapture(
"rtsp://192.168.0.10:554/user=admin&password=&channel=1&stream=0.sdp?"
)
#camera = cv2.VideoCapture("rtsp://*****:*****@192.168.0.26:554/PSIA/streaming/channels/301")
#camera = cv2.VideoCapture(0)
loop = True
# add knn library for detect chars
blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN(
) # attempt KNN training
if blnKNNTrainingSuccessful == False: # if KNN training was not successful
print(
"\nerror: KNN traning was not successful\n") # show error message
return
count = 0
# not very important, just iterating for license array haha
license = []
VER = np.zeros(VERIF)
for x in VER:
license.append("")
numlicense = ""
knn = 0
# Looping for Video
while (loop):
# grab the current frame
(grabbed, frame) = camera.read()
#frame = camera.read()
if args.get("video") and not grabbed:
break
# resize the frame and convert it to grayscale
imgOriginalScene = imutils.resize(frame)
imgGrayscale, imgThresh = pp.preprocess(imgOriginalScene)
cv2.imshow("threshold", imgThresh)
#imgOriginalScene = imutils.transform (imgOriginalScene)
imgOriginalScene, licenses = searching(imgOriginalScene, loop)
# only save 5 same license each time
license[count + 1] = licenses
nums = license[VERIF - 1]
if (license[count] == license[count + 1]):
license[count] = license[count + 1]
count = count + 1
elif (license[count] != license[count + 1]):
coba = license[count + 1]
count = 0
license[count] = coba
if count == (VERIF - 1):
'''
plateAlloc = " "
numstring = ""
numbers = sum(c.isdigit() for c in nums)
words = sum(c.isalpha() for c in nums)
for c in nums:
numstring.append()
'''
global plat
plat = " "
plat = list(plat)
numstring = ""
numstring = list(numstring)
alphastring = ""
alphastring = list(alphastring)
numbers = sum(c.isdigit() for c in nums)
words = sum(c.isalpha() for c in nums)
for i in nums:
#nums = np.array(nums)
#nums = list(nums)
if i.isalpha():
#nums[i] = np.array(nums[i])
alphastring.append(i)
elif i.isdigit():
#nums[i] = np.array(nums[i])
numstring.append(i)
print(nums)
print(numstring)
print(alphastring)
#add numbers
a = 2
for b in numstring:
plat[a] = b
a += 1
#add front letter(s)
c = 0
sumfront = sum(c.isalpha() for c in nums[0:2])
if (sumfront == 1):
for d in nums[0:1]:
plat[c] = d
c += 1
elif (sumfront == 2):
for d in nums[0:2]:
plat[c] = d
c += 1
#add back letter(s)
e = -3
sumback = sum(e.isalpha() for e in nums[-3:])
if (sumback == 1):
for f in nums[-1:]:
plat[e] = f
e += 1
elif (sumback == 2):
for f in nums[-2:]:
plat[e] = f
e += 1
elif (sumback == 3):
for f in nums[-3:]:
plat[e] = f
e += 1
plat = ''.join(plat)
if (license[VERIF - 1] == ""):
print("no characters were detected\n")
else:
#if number license same, not be saved
if (numlicense == license[VERIF - 1]):
print("still = " + numlicense + "\n")
elif (len(nums) <= 9 and nums[0] >= 'A' and nums[0] <= 'Z'
and numbers <= 4 and words <= 5):
numlicense = license[VERIF - 1]
#print("A new license plate read from image = " + license[VERIF-1] + "\n")
print("A new license plate read from image = " + plat +
"\n")
#cv2.imshow(license[VERIF-1], imgOriginalScene)
# cv2.imshow(plat, imgOriginalScene)
insertdata = data(numlicense)
if check(numlicense):
ts = time.time()
timestamp = datetime.datetime.fromtimestamp(
ts).strftime('%Y-%m-%d')
timestamp2 = datetime.datetime.fromtimestamp(
ts).strftime('%H:%M:%S')
#Ganti Path sesuai dengan laptop masing2 heheh
namefile = "/var/www/html/MonitoringDashboard/hasil_parksystem/" + license[
VERIF - 1] + timestamp + timestamp2 + ".png"
cv2.imwrite(namefile, imgOriginalScene)
#Hapus bagian ini untuk tidak menggunakan sensor dan mengirim mqtt
#broker="192.168.8.120"
#port=1883
#client1= paho.Client("control1") #create client object
#client1.connect(broker,port) #establish connection
#ret= client1.publish("xiaomi/to/write",'{"cmd": "write", "model": "plug", "sid": "158d0002365abb", "data": {"status": "on"}}')
# broker="192.168.1.151"
# port=1883
# client1= paho.Client("control1") #create client object
# client1.connect(broker,port) #establish connection
# client1.publish("alpr/mqtt","0")
# os.system('spd-say "Welcome to Graha Sumber Prima Elektronik"')
count = 0
#determine plate regions
# global plateRegion
# plateRegion = ""
# plateDic = {'B':"Jakarta", 'D':"Bandung", 'L':"Surabaya", 'A':"Banten", 'E':"Cirebon", 'G':"Pekalongan", 'H':"Semarang"}
# for i, j in plateDic.items():
# if (plat[0] == i):
# plateRegion = j
#and nums[0] >= 'A' and nums[0] <= 'Z' and nums[-1] >= 'A' and nums[-1] <= 'Z'
'''
global plateRegion
if (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'B'):
plateRegion = "Jakarta"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'D'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'E'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'D'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'D'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'D'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'D'):
plateRegion = "Bandung"
elif (len(nums) >= 5 and len(nums) <= 9 and nums[0] == 'L'):
plateRegion = "Surabaya"
else:
plateRegion = "Who knows?"
'''
#print(license)
# re-show scene image
#imgOriginalScene = cv2.blur(imgOriginalScene,(12,12))
cv2.putText(
imgOriginalScene,
"Press 's' to save frame to be 'save.png', for calibrating",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 255),
1,
bottomLeftOrigin=False)
#drawRedRectangleAroundPlate(imgOriginalScene, imgOriginalScene)
#cv2.rectangle(imgOriginalScene,((imgOriginalScene.shape[1]/2-230),(imgOriginalScene.shape[0]/2-80)),((imgOriginalScene.shape[1]/2+230),(imgOriginalScene.shape[0]/2+80)),SCALAR_GREEN,3)
cv2.rectangle(imgOriginalScene,
((int(imgOriginalScene.shape[1] / 2 - 230)),
(int(imgOriginalScene.shape[0] / 2 - 80))),
((int(imgOriginalScene.shape[1] / 2 + 230)),
(int(imgOriginalScene.shape[0] / 2 + 80))),
SCALAR_GREEN, 3)
cv2.imshow("imgOriginalScene", imgOriginalScene)
#cv2.imshow("ori", frame)
key = cv2.waitKey(5) & 0xFF
if key == ord('s'):
knn = str(knn)
savefileimg = "calib_knn/img_" + knn + ".png"
savefileThr = "calib_knn/Thr_" + knn + ".png"
#cv2.saveimage("save.png", imgOriginalScene)
cv2.imwrite(savefileimg, frame)
cv2.imwrite(savefileThr, imgThresh)
print("image save !")
knn = int(knn)
knn = knn + 1
if key == 27: # if the 'q' key is pressed, stop the loop
break
camera.release() # cleanup the camera and close any open windows
# For image only
if (loop == False):
imgOriginalScene = imutils.resize(imgOriginalScene, width=2000)
cv2.imshow("original", imgOriginalScene)
imgGrayscale, imgThresh = pp.preprocess(imgOriginalScene)
cv2.imshow("threshold", imgThresh)
#imgOriginalScene = imutils.transform (imgOriginalScene)
imgOriginalScene, license = searching(imgOriginalScene, loop)
#imgOriginalScene = imutils.detransform(imgOriginalScene)
cv2.waitKey(0)
cv2.waitKey(0)
cv2.destroyAllWindows()
return
def alpr(frame, sess, detection_graph):
# add knn library for detect chars
blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN() # attempt KNN training
if blnKNNTrainingSuccessful == False: # if KNN training was not successful
print("\nerror: KNN traning was not successful\n") # show error message
return
count = 0
# not very important, just iterating for license array haha
license = []
VER = np.zeros(VERIF)
for x in VER:
license.append("")
numlicense = ""
knn = 0
loop=True
# resize the frame and convert it to grayscale
imgOriginalScene = imutils.resize(frame)
imgGrayscale, imgThresh = pp.preprocess(imgOriginalScene)
#cv2.imshow("threshold", imgThresh)
#imgOriginalScene = imutils.transform (imgOriginalScene)
imgOriginalScene, licenses = searching(imgOriginalScene,loop)
# only save 5 same license each time
license[count+1] = licenses
nums = license[VERIF-1]
if (license[count] == license[count+1]):
license[count]=license[count+1]
count = count + 1
elif (license[count] != license[count+1]):
coba = license[count+1]
count = 0
license[count] = coba
if count == (VERIF-1):
'''
plateAlloc = " "
numstring = ""
numbers = sum(c.isdigit() for c in nums)
words = sum(c.isalpha() for c in nums)
for c in nums:
numstring.append()
'''
global plat
plat = " "
plat = list(plat)
numstring = ""
numstring = list(numstring)
alphastring = ""
alphastring = list(alphastring)
numbers = sum(c.isdigit() for c in nums)
words = sum(c.isalpha() for c in nums)
for i in nums:
#nums = np.array(nums)
#nums = list(nums)
if i.isalpha():
#nums[i] = np.array(nums[i])
alphastring.append(i)
elif i.isdigit():
#nums[i] = np.array(nums[i])
numstring.append(i)
print(nums)
print(numstring)
print(alphastring)
#add numbers
a = 2
for b in numstring:
plat[a] = b
a+=1
#add front letter(s)
c = 0
sumfront = sum(c.isalpha() for c in nums[0:2])
if (sumfront == 1):
for d in nums[0:1]:
plat[c] = d
c+=1
elif (sumfront == 2):
for d in nums[0:2]:
plat[c] = d
c+=1
#add back letter(s)
e = -3
sumback = sum(e.isalpha() for e in nums[-3:])
if (sumback == 1):
for f in nums[-1:]:
plat[e] = f
e+=1
elif (sumback == 2):
for f in nums[-2:]:
plat[e] = f
e+=1
elif (sumback == 3):
for f in nums[-3:]:
plat[e] = f
e+=1
plat = ''.join(plat)
if (license[VERIF-1] == ""):
print("no characters were detected\n")
else:
#if number license same, not be saved
if (numlicense == license[VERIF-1]):
print("still = " + numlicense + "\n")
elif (len(nums) <= 9 and nums[0] >= 'A' and nums[0] <= 'Z' and numbers <= 4 and words <= 5):
numlicense = license[VERIF-1]
print("A new license plate read from image = " + plat + "\n")
insertdata= data(numlicense)
if check(numlicense):
ts = time.time()
timestamp = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timestamp2 = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
#Ganti Path sesuai dengan laptop masing2 heheh
namefile = "/var/www/html/MonitoringDashboard/hasil_parksystem/"+ license[VERIF-1] + timestamp + timestamp2 + ".png"
cv2.imwrite(namefile, imgOriginalScene)
#Hapus bagian ini untuk tidak menggunakan sensor dan mengirim mqtt
#broker="192.168.8.120"
#port=1883
#client1= paho.Client("control1") #create client object
#client1.connect(broker,port) #establish connection
#ret= client1.publish("xiaomi/to/write",'{"cmd": "write", "model": "plug", "sid": "158d0002365abb", "data": {"status": "on"}}')
# broker="192.168.1.151"
# port=1883
# client1= paho.Client("control1") #create client object
# client1.connect(broker,port) #establish connection
# client1.publish("alpr/mqtt","0")
# os.system('spd-say "Welcome to Graha Sumber Prima Elektronik"')
count = 0
cv2.putText(imgOriginalScene,"Press 's' to save frame to be 'save.png', for calibrating",(10,30),cv2.FONT_HERSHEY_SIMPLEX, 0.5,(255,255,255),1,bottomLeftOrigin = False)
cv2.rectangle(imgOriginalScene,((int(imgOriginalScene.shape[1]/2-230)),(int(imgOriginalScene.shape[0]/2-80))),((int(imgOriginalScene.shape[1]/2+230)),(int(imgOriginalScene.shape[0]/2+80))),SCALAR_GREEN,3)
try:
return dict(imgOriginalScenes=imgOriginalScene)
except:
return {}
from flask import Flask
from flask import render_template
from flask import request
from flask import session
from flask import redirect
from flask import url_for
from database import data
import json
import os
import re
app = Flask(__name__)
app.secret_key = os.urandom(16)
# Set database
db = data()
# Convert a list to a comma separated string
def li_to_str(li):
st = ""
if li != []:
st = ', '.join(li)
return st
# Process user's answers to form
def processform(f):
selections = {}
for key in f.keys():
import unittest
import match
import copy
import random
from database import data
# mode TEST
TEST = False
d = data()
guyprefers = d.guyprefers
galprefers = d.galprefers
capacity = d.capacity
class TestDeCase(unittest.TestCase):
"""Test la fiabilite du match"""
def setUp(self):
self.engaged, self.rejected = match.matchmaker(guyprefers, galprefers, capacity)
def test_1_check_stability(self):
"""Verifie que la stabilite du match"""
self.assertTrue(match.check(self.engaged, guyprefers, galprefers))
print('Engagement stability check PASSED'
if match.check(self.engaged, guyprefers, galprefers) else 'Engagement stability check FAILED')
print()
def test_2_check_instability(self):
"""Verifie l'instabilite du match si l'on introduit volontairement une erreur"""
for _ in range(10):
gals = self.engaged.keys()
def main():
# argument for input video/image/calibration
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to video file")
ap.add_argument("-i", "--image", help="Path to the image")
ap.add_argument("-c", "--calibration", help="image or video or camera")
args = vars(ap.parse_args())
if args.get("calibration", True):
imgOriginalScene = cv2.imread(args["calibration"])
if imgOriginalScene is None:
print("Please check again the path of image or argument !")
imgOriginalScene = imutils.resize(imgOriginalScene, width=640)
cal.calibration(imgOriginalScene)
return
if args.get("video", True):
camera = cv2.VideoCapture(args["video"])
if camera is None:
print(" Please check again the path of video or argument !")
loop = True
elif args.get("image", True):
imgOriginalScene = cv2.imread("tes_plat_indo/B6703WJF.jpg")
if imgOriginalScene is None:
print(" Please check again the path of image or argument !")
loop = False
else:
# 0 digunakan untuk camera laptop, 1 untuk camera external
camera = cv2.VideoCapture(0)
loop = True
# add knn library for detect chars
blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN(
) # attempt KNN training
if blnKNNTrainingSuccessful == False: # if KNN training was not successful
print(
"\nerror: KNN traning was not successful\n") # show error message
return
count = 0
# not very important, just iterating for license array haha
license = []
VER = np.zeros(VERIF)
for x in VER:
license.append("")
numlicense = ""
susi = ""
knn = 0
# Looping for Video
while (loop):
# grab the current frame
(grabbed, frame) = camera.read()
#frame = camera.read()
if args.get("video") and not grabbed:
break
# resize the frame and convert it to grayscale
imgOriginalScene = imutils.resize(frame)
imgGrayscale, imgThresh = pp.preprocess(imgOriginalScene)
cv2.imshow("threshold", imgThresh)
# imgOriginalScene = imutils.transform (imgOriginalScene)
imgOriginalScene, licenses = searching(imgOriginalScene, loop)
# only save 5 same license each time
license[count + 1] = licenses
nums = license[VERIF - 1]
if (license[count] == license[count + 1]):
license[count] = license[count + 1]
count = count + 1
elif (license[count] != license[count + 1]):
coba = license[count + 1]
count = 0
license[count] = coba
if count == (VERIF - 1):
global plat
plat = " "
plat = list(plat)
numstring = ""
numstring = list(numstring)
alphastring = ""
alphastring = list(alphastring)
numbers = sum(c.isdigit() for c in nums)
words = sum(c.isalpha() for c in nums)
for i in nums:
if i.isalpha():
alphastring.append(i)
elif i.isdigit():
numstring.append(i)
print(nums)
print(numstring)
print(alphastring)
#add numbers
a = 2
for b in numstring:
plat[a] = b
a += 1
#add front letter(s)
c = 0
sumfront = sum(c.isalpha() for c in nums[0:2])
if (sumfront == 1):
for d in nums[0:1]:
plat[c] = d
c += 1
elif (sumfront == 2):
for d in nums[0:2]:
plat[c] = d
c += 1
#add back letter(s)
e = -3
sumback = sum(e.isalpha() for e in nums[-3:])
if (sumback == 1):
for f in nums[-1:]:
plat[e] = f
e += 1
elif (sumback == 2):
for f in nums[-2:]:
plat[e] = f
e += 1
elif (sumback == 3):
for f in nums[-3:]:
plat[e] = f
e += 1
plat = ''.join(plat)
if (license[VERIF - 1] == ""):
print("no characters were detected\n")
else:
#if number license same, not be saved
if (numlicense == license[VERIF - 1]):
print("still = " + numlicense + "\n")
elif (len(nums) <= 9 and nums[0] >= 'A' and nums[0] <= 'Z'
and numbers <= 4 and words <= 5):
numlicense = license[VERIF - 1]
print(license[VERIF - 1])
print(numlicense)
print("A new license plate read from image = " + plat +
"\n")
insertdata = data(numlicense)
print(insertdata)
if check(numlicense):
ts = time.time()
timestamp = datetime.datetime.fromtimestamp(
ts).strftime('%Y-%m-%d')
timestamp2 = datetime.datetime.fromtimestamp(
ts).strftime('%H:%M:%S')
#Ganti Path sesuai dengan laptop masing2
namefile = "/Documents/" + license[
VERIF - 1] + timestamp + timestamp2 + ".png"
cv2.imwrite(namefile, imgOriginalScene)
count = 0
cv2.putText(
imgOriginalScene,
"Press 's' to save frame to be 'save.png', for calibrating",
(10, 30),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 255),
1,
bottomLeftOrigin=False)
#drawRedRectangleAroundPlate(imgOriginalScene, imgOriginalScene)
#cv2.rectangle(imgOriginalScene,((imgOriginalScene.shape[1]/2-230),(imgOriginalScene.shape[0]/2-80)),((imgOriginalScene.shape[1]/2+230),(imgOriginalScene.shape[0]/2+80)),SCALAR_GREEN,3)
cv2.rectangle(imgOriginalScene,
((int(imgOriginalScene.shape[1] / 2 - 230)),
(int(imgOriginalScene.shape[0] / 2 - 80))),
((int(imgOriginalScene.shape[1] / 2 + 230)),
(int(imgOriginalScene.shape[0] / 2 + 80))),
SCALAR_GREEN, 3)
cv2.imshow("imgOriginalScene", imgOriginalScene)
key = cv2.waitKey(5) & 0xFF
if key == ord('s'):
knn = str(knn)
savefileimg = "calib_knn/img_" + knn + ".png"
savefileThr = "calib_knn/Thr_" + knn + ".png"
#cv2.saveimage("save.png", imgOriginalScene)
cv2.imwrite(savefileimg, frame)
cv2.imwrite(savefileThr, imgThresh)
print("image save !")
knn = int(knn)
knn = knn + 1
if key == 27: # if the 'q' key is pressed, stop the loop
break
camera.release() # cleanup the camera and close any open windows
# For image only
if (loop == False):
imgOriginalScene = imutils.resize(imgOriginalScene, width=2000)
cv2.imshow("original", imgOriginalScene)
imgGrayscale, imgThresh = pp.preprocess(imgOriginalScene)
cv2.imshow("threshold", imgThresh)
#imgOriginalScene = imutils.transform (imgOriginalScene)
imgOriginalScene, license = searching(imgOriginalScene, loop)
#imgOriginalScene = imutils.detransform(imgOriginalScene)
cv2.waitKey(0)
cv2.waitKey(0)
cv2.destroyAllWindows()
return
