def Start():
#Configuration de la page
config = {
"apiKey": "AIzaSyDk9Y_vRsmSB-_keAx-SbGOYncRjgkjbPQ",
"authDomain": "novastepdb.firebaseapp.com",
"databaseURL": "https://novastepdb.firebaseio.com",
"projectId": "novastepdb",
"storageBucket": "novastepdb.appspot.com",
"messagingSenderId": "14365121179",
"appId": "1:14365121179:web:cf2bdb7ff66b931b9a043e",
"measurementId": "G-PKCX76F1K8"
}
global pageActuelle
global pagePrecedente
pageActuelle = "Accueil"
pagePrecedente = ""
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
storage.child("images/new.jpg").download("jamgeTendue.png")
storage.child("images/new1.jpg").download("jambePlié.png")
clean()
#Items ajoutés
logoAccueil_label.place(x=logoAccueil_label_x, y=logoAccueil_label_y)
bouton_start.place(x=Coord_Bouton_Centr[0], y=Coord_Bouton_Centr[1])
def uploadwithPyre(self, filepath, secretkey, id):
table = self.table
cred['private_key'] = secretkey
config = {
"apiKey": "apiKey",
"authDomain": "hepatitis-mobile.firebaseapp.com",
"databaseURL": "https://hepatitis-mobile.firebaseio.com",
"storageBucket": "hepatitis-mobile.appspot.com",
"serviceAccount": cred
}
storage_path = f'image/patient/{id}/'
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
storage.child(storage_path).put(filepath)
imageurl = storage.child(storage_path).get_url(id)
with connection.cursor() as cursor:
query = f"UPDATE {table} SET imgurl = {repr(imageurl)} WHERE {table}.id={repr(id)}"
try:
cursor.execute(query)
connection.commit()
return ("upload successful")
except:
return ("unable to upload image")
def urlprocess(url):
name = url
# print(name.find("%2F"));
path = name[name.find("%2F")+3:]
path =path[:path.find("%2F")]
# print(path)
tokens = name[name.find("token=")+6:]
# auth = firebase.auth()
# tokens = auth.sign_in_with_email_and_password("*****@*****.**","Teo361812")
# tokens = auth.refresh(tokens['refreshToken'])
# print(tokens)
# print (name)
firebasepath = "images/" + "{}".format(path)+"/{}.jpg".format(path)
# print(firebasepath)
storage = firebase.storage()
# print(storage.child(firebasepath).get_url(tokens))
storage.child(firebasepath).download("newimage.jpg")
# hardcode xd
# img_path = "./newimage.jpg"
# pre_img_path = 'pre_' + os.path.basename(img_path) # pre_0.jpg
# command = './imgtxtenh/imgtxtenh ' + ' -p ' + os.path.basename(img_path) + " " + os.path.basename(pre_img_path)# ../../imgtxtenh/imgtxtenh 0.jpg -p pre_0.jpg
# p = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE)
uploadpath = "images/"+ "{}".format(path) + "/ocr.jpg"
global ocrpath
ocrpath = uploadpath
def photo():
img = Image.open(request.files['img'])
try:
filename = secure_filename(request.files['img'].filename)
print(filename)
#img = img.resize((160,300),Image.ANTIALIAS)
img.save(filename, optimize=True, quality=70)
print(img)
storage.child("images/" + filename).put(img)
#link=storage.child("images/"+filename).get_url(None)
#print(link)
return jsonify({'message': link}), 200
except:
return jsonify({'message': 'error in uploading image'}), 400
def saveFolder(uploaded_files):
cwd = os.getcwd()
config = {"apiKey": "xxxxx",
"authDomain": "xxxxx.firebaseapp.com",
"databaseURL": "https://xxxxx.firebaseio.com",
"projectId": "xxxxx",
"storageBucket": "xxxxx.appspot.com",
"messagingSenderId": "xxxxx",
"appId": "1:xxxxx:web:xxxxx",
"measurementId": "G-FXCMDZNL6T"}
for folder in uploaded_files:
if type(folder) == list:
saveFolder(folder)
else:
path = os.path.join('./test/test', folder.filename)
folder_path = f'{folder.filename.split("/")[:-1]}'
folder_path = folder_path[2:-2]
folder_path = folder_path.replace("\', \'", "/")
filePath = f"{cwd}/test/test/{folder_path}"
if os.path.exists(filePath) == True:
folder.save(f'{filePath}/{folder.filename.split("/")[-1]}')
else:
os.mkdir(filePath)
folder.save(f'{filePath}/{folder.filename.split("/")[-1]}')
#save to firebase
today = datetime.now()
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
path_on_cloud = f'images/{today}.jpg'
storage.child(path_on_cloud).put(f'{filePath}/{folder.filename.split("/")[-1]}')
upload_url = storage.child(path_on_cloud).get_url(token=None)
'''
def __init__(self):
super().__init__()
self.setWindowTitle("TIP")
self.setGeometry(800, 200, 600, 630) #크기설정 (x좌표,y좌표,너비,높이)
#메뉴 최대 갯수 지정
self.btnnum = [
'1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12',
'13', '14', '15', '16', '17', '18', '19', '20'
]
self.btnlist = []
self.Piclist = []
for i in range(0, len(name)):
storage.child(path_on_cloud + str(i + 1) + ".jpg").download(
"img" + str(i + 1) + ".jpg",
str(i + 1) + ".jpg")
self.Piclist.append(PicButton(QPixmap(self.btnnum[i] + '.jpg')))
self.Piclist[i].setMaximumHeight(100)
self.Piclist[i].setMaximumWidth(100)
self.btnlist.append(QPushButton(name[i]))
self.btnlist[i].clicked.connect(lambda state, button=self.btnlist[
i]: self.btn_clicked(state, button))
self.Obtn1 = QPushButton("주문하기")
self.Obtn1.setMaximumHeight(150)
self.Obtn1.clicked.connect(self.btn_order)
self.Obtn2 = QPushButton("취소하기")
self.Obtn2.setMaximumHeight(150)
self.Obtn2.clicked.connect(self.btn_refresh)
layout1 = QGridLayout() #GUI 컨텐츠들을 배치할 레이아웃 설정
for i in range(0, len(name)):
layout1.addWidget(self.Piclist[i], math.floor(i / 4) * 2, i % 4)
layout1.addWidget(self.btnlist[i],
math.floor(i / 4) * 2 + 1, i % 4)
groupbox = QGroupBox("주문정보") #그룹박스 추가
self.tableWidget = QTableWidget(4, 2) #테이블 생성
self.tableWidget.setHorizontalHeaderLabels(["음식이름",
"가격"]) #식당이름까지 DB로 보냄
self.tableWidget.setMaximumHeight(160) #테이블의 높이
self.tableWidget.setMaximumWidth(250) #테이블의 너비
self.tableWidget.horizontalHeader().setStretchLastSection(
True) #글자가 넘어갔을때 글자가 ...으로 나오지 않도록 설정
layout2 = QHBoxLayout() #레이아웃 추가
layout2.addWidget(self.tableWidget) #테이블및 버튼추가
layout2.addWidget(self.Obtn1)
layout2.addWidget(self.Obtn2)
groupbox.setLayout(layout2)
layout3 = QHBoxLayout()
layout3.addWidget(groupbox)
layout = QVBoxLayout()
layout.addLayout(layout1)
layout.addLayout(layout3)
self.setLayout(layout) #레이아웃 합침
def trackImages():
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("Python-Code/DataSet/Trainner.yml")
# harcascadePath = "haarcascade_frontalface_default.xml"
# faceCascade = cv2.CascadeClassifier(harcascadePath)
faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades +
'haarcascade_frontalface_default.xml')
df = pd.read_csv("StudentRecord.csv")
cam = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id', 'Name', 'Date', 'Time']
attendance = pd.DataFrame(columns=col_names)
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x + w, y + h), (225, 0, 0), 2)
Id, conf = recognizer.predict(gray[y:y + h, x:x + w])
if (conf < 50):
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime(
'%H:%M:%S')
aa = df.loc[df['Id'] == Id]['Name'].values
tt = str(Id) + "-" + aa
attendance.loc[len(attendance)] = [Id, aa, date, timeStamp]
# cv2.putText(im, "Name: " + str(df.loc['Name'].values), (x,y+h+30), fontface, fontscale, fontcolor ,2)
else:
Id = 'Unknown'
tt = str(Id)
if (conf > 75):
noOfFile = len(os.listdir("Python-Code/UnknownImages")) + 1
cv2.imwrite(
"Python-Code/UnknownImages/Image" + str(noOfFile) + ".jpg",
im[y:y + h, x:x + w])
cv2.putText(im, str(tt), (x, y + h), font, 1, (255, 255, 255), 2)
attendance = attendance.drop_duplicates(subset=['Id'], keep='first')
cv2.imshow('Face Recognizing', im)
if cv2.waitKey(10000) == ord('q'):
break
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
Hour, Minute, Second = timeStamp.split(":")
#fileName="Attendance\Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
fileName = "Python-Code/Attendance/Attendance_" + date + "_" + Hour + "-" + Minute + ".csv"
attendance.to_csv(fileName, index=False)
Firebase = pyrebase.initialize_app(config)
storage = Firebase.storage()
blob = storage.child('uploads1/' + fileName).put(fileName)
data = {
'name':
"Date_" + date + " Time_" + Hour + "-" + Minute + "-" + Second,
'url':
"https://console.firebase.google.com/u/6/project/facereconition-431f9/storage/facereconition-431f9.appspot.com/files~2Fuploads1~2FPython-Code~2FAttendance%5CAttendance_"
+ date + "_" + Hour + "-" + Minute + ".csv?alt=media&token=" +
blob['downloadTokens']
}
#data = { 'name': "Date_"+date+" Time_"+Hour+"-"+Minute+"-"+Second, 'url': ULR stograge to uploade file excel(.csv) }
result = firebase.post('facereconition-431f9-default-rtdb/uploads1/',
data) #databaseURL + folder you create
print(result)
cam.release()
cv2.destroyAllWindows()
res = attendance
message.configure(text=res)
'messagingSenderId': "429388420685",
'appId': "1:429388420685:web:7070e74b7130f11fcdae04",
'measurementId': "G-MN3PGPLFZD"
}
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
LANGUAGE = 'english'
with open('data/recognized.txt', 'r') as input_file:
SENTENCES_COUNT = int(n_sentences(input_file.read()) * .4)
with open('data/recognized.txt', 'r') as file:
data = file.read().replace('\n', '')
storage.child('app/input').download(path='backend/data/app/input.jpeg',
filename='data/app/input.jpeg')
storage.child('website/input').download(path='backend/data/website/input.jpeg',
filename='data/website/input.jpeg')
storage.child('website/audio').download(path='backend/data/website/input.wav',
filename='data/website/input.wav')
#------------------------------
INPUT = 'data/app/input.jpeg'
#---------------------------------
create_input(INPUT)
parser = PlaintextParser.from_string(data, Tokenizer(LANGUAGE))
stemmer = Stemmer(LANGUAGE)
def trackImages():
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("DataSet\Trainner.yml")
harcascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadePath)
df = pd.read_csv("StudentRecord.csv")
cam = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id', 'Name', 'Date', 'Time']
attendance = pd.DataFrame(columns=col_names)
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.2, 5)
for (x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x + w, y + h), (225, 0, 0), 2)
Id, conf = recognizer.predict(gray[y:y + h, x:x + w])
if (conf < 50):
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime(
'%H:%M:%S')
aa = df.loc[df['Id'] == Id]['Name'].values
tt = str(Id) + "-" + aa
attendance.loc[len(attendance)] = [Id, aa, date, timeStamp]
else:
Id = 'Unknown'
tt = str(Id)
if (conf > 75):
noOfFile = len(os.listdir("UnknownImages")) + 1
cv2.imwrite("UnknownImages\Image" + str(noOfFile) + ".jpg",
im[y:y + h, x:x + w])
cv2.putText(im, str(tt), (x, y + h), font, 1, (255, 255, 255), 2)
attendance = attendance.drop_duplicates(subset=['Id'], keep='first')
cv2.imshow('Face Recognizing', im)
pass
if cv2.waitKey(10000):
break
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
Hour, Minute, Second = timeStamp.split(":")
#fileName="Attendance\Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
fileName = "Attendance\Attendance_" + date + "_" + Hour + "-" + Minute + ".csv"
attendance.to_csv(fileName, index=False)
Firebase = pyrebase.initialize_app(config)
storage = Firebase.storage()
blob = storage.child('uploads/' + fileName).put(fileName)
#jay = storage.child().get_url(blob['downloadTokens'])
data = {
'name':
"Date_" + date + " Time_" + Hour + "-" + Minute + "-" + Second,
'url':
"gs://attendecesystem-62b04.appspot.com/uploads/%2FAttendance%5CAttendance_"
+ date + "_" + Hour + "-" + Minute + ".csv?alt=media&token=" +
blob['downloadTokens']
}
#data = { 'name': "Date_"+date+" Time_"+Hour+"-"+Minute+"-"+Second, 'url': jay}
result = firebase.post('/uploads', data)
print(result)
cam.release()
cv2.destroyAllWindows()
# Enable Storage
from firebase import firebase
import pyrebase
config = {
"apiKey": " AIzaSyD_aONTpekw50_3RlNtt-LApnVuO2kisbM ",
"authDomain": "plant-7de21.firebaseapp.com",
"databaseURL": "https://plant-7de21.firebaseio.com/",
#"projectId": "",
"storageBucket": "plant-7de21.appspot.com",
}
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
storage.child("Disease\Disease_Report.docx").put("Disease_Report.docx")
#firebase_admin.App("Plant",cred,"Default")
#firebase_admin.initialize_app(cred)
#firebase_admin.initialize_app(credential=None, options=None, name='[DEFAULT]')
#firebase_admin.get_app("Plant")
# Reference an existing bucket.
# Upload a local file to a new file to be created in your bucket.
#zebraBlob = bucket.get_blob('zebra.jpg')
#zebraBlob.upload_from_filename(filename='/photos/zoo/zebra.jpg')
# Download a file from your bucket.
#giraffeBlob = bucket.get_blob('giraffe.jpg')
#giraffeBlob.download_as_string()
"databaseURL": "https://facebookchat-f1db0.firebaseio.com",
"projectId": "facebookchat-f1db0",
"storageBucket": "facebookchat-f1db0.appspot.com",
"messagingSenderId": "932350125174",
"appId": "1:932350125174:web:eb6542aa2fca8177d36b57",
"measurementId": "G-FXWBB6W7P3"
}
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
path_on_cloud = "output/output"
path_local = "output/output.png"
path_for_input = "yogaImages/yoga"
storage.child(path_for_input).download("input/input.png")
parser = argparse.ArgumentParser()
parser.add_argument('--input', help='Path to image or video. Skip to capture frames from camera')
parser.add_argument('--thr', default=0.2, type=float, help='Threshold value for pose parts heat map')
parser.add_argument('--width', default=368, type=int, help='Resize input to specific width.')
parser.add_argument('--height', default=368, type=int, help='Resize input to specific height.')
args = parser.parse_args()
BODY_PARTS = { "Nose": 0, "Neck": 1, "RShoulder": 2, "RElbow": 3, "RWrist": 4,
"LShoulder": 5, "LElbow": 6, "LWrist": 7, "RHip": 8, "RKnee": 9,
"RAnkle": 10, "LHip": 11, "LKnee": 12, "LAnkle": 13, "REye": 14,
"LEye": 15, "REar": 16, "LEar": 17, "Background": 18 }
POSE_PAIRS = [ ["Neck", "RShoulder"], ["Neck", "LShoulder"], ["RShoulder", "RElbow"],
try:
switch = 1
while True:
now = datetime.now()
if switch:
#sens = DLsensor.mtreg
#hr = DLsensor.measure_high_res()
#hr2 = DLsensor.measure_high_res2()
lumi = DLsensor.measure_low_res()
DLsensor.set_sensitivity((DLsensor.mtreg + 10) % 255)
# Try to grab a sensor reading. Use the read_retry method which will retry up
# to 15 times to get a sensor reading (waiting 2 seconds between each retry).
humi, temp = Adafruit_DHT.read_retry(DHTsensor, DHTpin)
print(dbUpdate(now, lumi, temp, humi))
switch = 0
else:
filename = 'img_' + now.strftime('%Y-%m-%d_%H:%M:%S') + '.jpg'
single_frame(filename, 10)
time.sleep(10)
print(storage.child(path_on_cloud).put("images/" + filename))
# print(imageUp(now, filename))
switch = 1
time.sleep(delay / 2)
except (KeyboardInterrupt, SystemExit):
print(" -> Ambient Control program shutdown...")
print("Bye!")
sys.exit()
def upload_to_firebase(filename):
file_path = f"./results/{filename}"
file_node = storage.child(filename)
result = file_node.put(file_path)
url = build_download_url(result["name"], result["downloadTokens"])
return url
from google.cloud import storage
from firebase import firebase
import os
import urllib
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'visker-ede34-firebase-adminsdk-u8kfs-adeefaeb4f.json'
firebase=firebase.FirebaseApplication('https://visker-ede34.appspot.com/')
client=storage.Client()
bucket=client.get_bucket('visker-ede34.appspot.com')
blobs=bucket.list_blobs()
imageBlob=bucket.blob("images/1.jpg")
imageBlob.upload_from_filename('thor.jpg')
imageBlob=bucket.blob("images/2.jpg")
imageBlob.upload_from_filename('image.jpg')
storage = firebase.storage()
storage.child("images/example.jpg").download("img")
def predictOneImage():
if request.method == "POST":
img_url = request.files["image"]
apikey = request.form["apikey"]
print(f'this is the url {img_url.filename}')
if img_url.filename == "":
flash('Please upload an image')
return redirect(url_for("folderImagesPredict"))
else:
UPLOAD_FOLDER = './test/test'
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
#save image to local directory for upload to firebase storage
path = os.path.join(app.config['UPLOAD_FOLDER'], img_url.filename)
img_url.save(path)
if not firebase_admin._apps:
#fetch credentials
cred = credentials.Certificate("service_account.json")
firebase_admin.initialize_app(cred, {'databaseURL': 'https://xxxxx.firebaseio.com/'})
##validate API KEY
ref = db.reference('ApiKey')
apiKeyType = ref.child(apikey).child("type").get()
if apiKeyType == None:
flash('Invalid API Key')
return redirect(url_for("oneImagePredict"))
else:
#image_url = sys.argv[1] #we pass the url as an argument
config = {"apiKey": "xxxxx",
"authDomain": "xxxxx.firebaseapp.com",
"databaseURL": "https://xxxxx.firebaseio.com",
"projectId": "xxxxx",
"storageBucket": "xxxxx.appspot.com",
"messagingSenderId": "xxxxx",
"appId": "1:xxxxx:web:xxxxx",
"measurementId": "xxxxx"}
today = datetime.now()
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
path_on_cloud = f'images/{today}.jpg'
storage.child(path_on_cloud).put(path)
upload_url = storage.child(path_on_cloud).get_url(token=None)
#Download Image
'''
with urllib.request.urlopen(upload_url) as url:
with open('test/temp.jpg', 'wb') as f:
f.write(url.read())
'''
#preprocess image
test_gen = ImageDataGenerator(rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_generator = test_gen.flow_from_directory(
"test/",
target_size=(224, 224),
shuffle = False,
class_mode='categorical',
batch_size=1)
#load model
loaded_model = load_model('model/model1-94%.h5')
#make prediciton
predict = loaded_model.predict_generator(test_generator)
array = np.array(predict)
ind = np.argmax(predict)
_class = ind
print(array,ind,_class)
#remove image from local directory
os.remove(path)
#return class
if _class == 0:
flash("BAD BACKGROUND")
return redirect(url_for("oneImagePredict"))
elif _class == 1:
flash("BLURRY")
return redirect(url_for("oneImagePredict"))
elif _class == 2:
flash("FACE IN BACKGROUND")
return redirect(url_for("oneImagePredict"))
elif _class == 3:
flash("GOOD IMAGE")
return redirect(url_for("oneImagePredict"))
elif _class == 4:
flash("INVALID PASSPORT")
return redirect(url_for("oneImagePredict"))
elif _class == 5:
flash("NO HUMAN FACE")
return redirect(url_for("oneImagePredict"))
elif _class == 6:
flash("STAPLE DEFACED")
return redirect(url_for("oneImagePredict"))
else:
return "500"
else:
return "Use a POST request to access this API, check documentation at "
def predictImagesInFolder():
if request.method == "POST":
uploaded_files = request.files.getlist("image")
apikey = request.form["apikey"]
if not uploaded_files or not any(f for f in uploaded_files):
flash('Please upload a folder')
return redirect(url_for("multipleImagePredict"))
else:
config = {"apiKey":xxxxx",
"authDomain": "xxxxx.firebaseapp.com",
"databaseURL": "xxxxx.firebaseio.com",
"projectId": "xxxxx",
"storageBucket": "xxxxx.appspot.com",
"messagingSenderId": "xxxxx",
"appId": "1:xxxxx:web:xxxxx",
"measurementId": "xxxxx"}
UPLOAD_FOLDER = './test/test'
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
saveFolder(uploaded_files)
if not firebase_admin._apps:
#fetch credentials
cred = credentials.Certificate("service_account.json")
firebase_admin.initialize_app(cred, {'databaseURL': 'https://xxxxx.firebaseio.com/'})
##validate API KEY
ref = db.reference('ApiKey')
apiKeyType = ref.child(apikey).child("type").get()
if apiKeyType == None:
flash('Invalid API Key')
return redirect(url_for("oneImagePredict"))
else:
#preprocess image
test_gen = ImageDataGenerator(rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_generator = test_gen.flow_from_directory(
"test/",
target_size=(224, 224),
shuffle = False,
class_mode='categorical',
batch_size=1)
#load model
loaded_model = load_model('model/model1-94%.h5')
#make prediciton
predict = loaded_model.predict_generator(test_generator)
array = np.array(predict)
result = {}
for i, rows in enumerate(array):
_class = np.argmax(rows)
result[uploaded_files[i].filename] = _class
today = datetime.now()
current_directory = os.getcwd()
final_directory = os.path.join(current_directory, f'result_{today}')
if not os.path.exists(final_directory):
os.makedirs(final_directory)
error = 0
currentProgress = 0
resultDisplayed = {}
for key, value in result.items():
if value == 0:
#BAD BACKGROUND
if os.path.exists(f"{final_directory}/BAD_BACKGROUND") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/BAD_BACKGROUND")
resultDisplayed["BAD_BACKGROUND"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/BAD_BACKGROUND")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/BAD_BACKGROUND")
resultDisplayed["BAD_BACKGROUND"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 1:
#BLURRY
if os.path.exists(f"{final_directory}/BLURRY") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/BLURRY")
resultDisplayed["BLURRY"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/BLURRY")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/BLURRY")
resultDisplayed["BLURRY"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 2:
#FACE_IN_BACKGROUND
if os.path.exists(f"{final_directory}/FACE_IN_BACKGROUND") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/FACE_IN_BACKGROUND")
resultDisplayed["FACE_IN_BACKGROUND"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/FACE_IN_BACKGROUND")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/FACE_IN_BACKGROUND")
resultDisplayed["FACE_IN_BACKGROUND"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 3:
#GOOD_IMAGES
if os.path.exists(f"{final_directory}/GOOD_IMAGES") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/GOOD_IMAGES")
resultDisplayed["GOOD_IMAGES"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/GOOD_IMAGES")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/GOOD_IMAGES")
resultDisplayed["GOOD_IMAGES"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 4:
#INVALID_PASSPORT
if os.path.exists(f"{final_directory}/INVALID_PASSPORT") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/INVALID_PASSPORT")
resultDisplayed["INVALID_PASSPORT"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/INVALID_PASSPORT")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/INVALID_PASSPORT")
resultDisplayed["INVALID_PASSPORT"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 5:
#NO_HUMAN_FACE
if os.path.exists(f"{final_directory}/NO_HUMAN_FACE") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/NO_HUMAN_FACE")
resultDisplayed["NO_HUMAN_FACE"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/NO_HUMAN_FACE")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/NO_HUMAN_FACE")
resultDisplayed["NO_HUMAN_FACE"] = 1
except Exception as e:
error += 1
currentProgress +=1
elif value == 6:
#STAPLED_FACE
if os.path.exists(f"{final_directory}/STAPLED_FACE") == True:
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/STAPLED_FACE")
resultDisplayed["STAPLED_FACE"] += 1
except:
error += 1
else:
#make directory
os.mkdir(f"{final_directory}/STAPLED_FACE")
try:
shutil.move(f"{UPLOAD_FOLDER}/{key}" , f"{final_directory}/STAPLED_FACE")
resultDisplayed["STAPLED_FACE"] = 1
except Exception as e:
error += 1
currentProgress +=1
#make zip file
shutil.make_archive(f'result_{today}', 'zip', final_directory)
#upload to firebase
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
path_on_cloud = f'results/{today}.zip'
storage.child(path_on_cloud).put(f'{final_directory}.zip')
upload_url = storage.child(path_on_cloud).get_url(token=None)
resultDisplayed["downloadLink"] = upload_url
print(f'result directory {upload_url}')
print(result)
#remove image from local directory
shutil.rmtree(final_directory)
os.remove(f'{final_directory}.zip')
return render_template("multipleFolderImagesPopUp.html", data=resultDisplayed)
else:
return "Use a POST request to access this API, check documentation at "
def RecognizeFaceFromVideo():
FaceRecognize = cv2.face.LBPHFaceRecognizer_create()
FaceRecognize.read("AllData\TrainedData\DataTrained.yml")
harcascadeFilePath = "AllData\haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadeFilePath)
datafile = pd.read_csv("AllData\StudentDataRecord.csv")
collum_names = ['Id', 'Name', 'Date', 'Time']
AttendanceOfStudent = pd.DataFrame(columns=collum_names)
cap = cv2.VideoCapture(0)
if (cap.isOpened() == False):
messagebox.showerror(
title="Error",
message="There is some problem with your camera")
root.destroy()
while True:
_, img = cap.read()
if (_ == False):
messagebox.showerror(
title="Error",
message=
"You have to close video running on home page or select image checkbox"
)
root.destroy()
break
grayImg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
Detectedfaces = faceCascade.detectMultiScale(grayImg, 1.2, 5)
for (x, y, width, height) in Detectedfaces:
cv2.rectangle(img, (x, y), (x + width, y + height),
(225, 0, 0), 2)
Id, confidence = FaceRecognize.predict(grayImg[y:y + height,
x:x + width])
if (confidence <= 50):
CurrentTime = time.time()
CurrentDate = datetime.datetime.fromtimestamp(
CurrentTime).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(
CurrentTime).strftime('%H:%M:%S')
name = datafile.loc[datafile['Id'] == Id]['Name'].values
key = str(Id) + "-" + name
AttendanceOfStudent.loc[len(AttendanceOfStudent)] = [
Id, name, CurrentDate, timeStamp
]
else:
Id = 'Unknown'
key = str(Id)
cv2.putText(img, str(key), (x, y + height),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
AttendanceOfStudent = AttendanceOfStudent.drop_duplicates(
subset=['Id'], keep='first')
cv2.imshow('Face Recognizing', img)
if cv2.waitKey(10000) or cv2.waitKey(1) == ord('q'):
break
CurrentTime = time.time()
CurrentDate = datetime.datetime.fromtimestamp(CurrentTime).strftime(
'%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(CurrentTime).strftime(
'%H:%M:%S')
Hour, Minute, Second = timeStamp.split(":")
fileName = "AllData\StudentAttendance\StudentAttendance_" + \
CurrentDate+"_"+Hour+"-"+Minute+".csv"
AttendanceOfStudent.to_csv(fileName, index=True)
Firebase = pyrebase.initialize_app(firebaseConfig)
storage = Firebase.storage()
bllob = storage.child('uploads/' + fileName).put(fileName)
StudentData = {
'name':
"Date: " + CurrentDate + " Time: " + Hour + "-" + Minute + "--" +
Second,
'url':
"https://firebasestorage.googleapis.com/v0/b/ <gs:add your firebase storage url here/> %2FAttendance%5CAttendance_"
+ CurrentDate + "_" + Hour + "-" + Minute +
".csv?alt=media&token=" + bllob['downloadTokens']
}
UploadDataToDatabase = firebase.post('/uploads', StudentData)
retrivedData = AttendanceOfStudent
StudentsPresent.configure(text=retrivedData)
cap.release()
cv2.destroyAllWindows()