def __init__(self, mode, network, network_criterion, n_clusters,
clustering_criterion, cluster_update_interval,
no_of_clustering_channels, n_epochs, no_of_pretrain_epochs,
batch_size, lr, alpha, downsampling_step, sequence_length,
kernel_size):
self.mode = mode
self.network = network
self.network_criterion = network_criterion
self.n_clusters = n_clusters
self.clustering_criterion = clustering_criterion
self.cluster_update_interval = cluster_update_interval
self.no_of_clustering_channels = no_of_clustering_channels
self.n_epochs = n_epochs
self.no_of_pretrain_epochs = no_of_pretrain_epochs
self.batch_size = batch_size
self.lr = lr
self.alpha = alpha
self.downsampling_step = downsampling_step
self.sequence_length = sequence_length
self.kernel_size = kernel_size
self.path = './{} N{} NC{} Ncl{} CUI{} NclCh{} E{} PE{} BS{} LR{} A{} DS{} SL{} KS{}'.format(
self.mode, self.network.__class__.__name__, self.network_criterion,
self.n_clusters, self.cluster_update_interval,
self.no_of_clustering_channels, self.n_epochs,
self.no_of_pretrain_epochs, self.batch_size, self.lr, self.alpha,
self.downsampling_step, self.sequence_length, self.kernel_size)
functions.createFolder(self.path)
def createadmin_submit1():
createFolder('./AdminDetails')
try:
if os.path.exists('./AdminDetails/admin_details.csv'):
print('Details directory already exists')
else:
print("Details directory doesn't Exist")
with open('./AdminDetails/admin_details.csv',
'w') as file:
writer = csv.writer(file)
writer.writerow([
"AdminIds", "AdminUserNames",
"AdminPhoneNumbers", "AdminEmailIds",
"AdminPasswords"
])
print(
"Creating new directory for employee_details.csv.")
except OSError:
print("File Already Exists")
AdminId = admin_id_entry.get()
AdminUserName = admin_username_entry.get()
AdminPhoneNumber = admin_phonenumber_entry.get()
AdminEmailId = admin_emailid_entry.get()
AdminPassword = admin_password_entry.get()
df = pd.read_csv('./AdminDetails/admin_details.csv')
if int(AdminId) in df['AdminIds'].values:
output.delete(0.0, END)
output.insert(END,
'Database Error: Admin ID Already Exists')
elif len(AdminPhoneNumber) != 10:
output.delete(0.0, END)
output.insert(
END, 'Input Validation Error: Wrong Phone Number')
elif int(AdminPhoneNumber) in df['AdminPhoneNumbers'].values:
output.delete(0.0, END)
output.insert(
END, 'Database Error: Phone Number Already Exist')
elif AdminEmailId in df['AdminEmailIds'].values:
output.delete(0.0, END)
output.insert(END,
'Database Error: Email Id Already Exist')
else:
output.delete(0.0, END)
try:
createadmin(AdminId, AdminUserName, AdminPhoneNumber,
AdminEmailId, AdminPassword)
output_string = 'New Admin Created: ' + AdminUserName
except:
output_string = "Failed to create Admin"
output.insert(END, output_string)
def modelTrainer():
print('\nModule Versions: ')
print('OpenCv: ' + cv2.__version__, '\nNumpy: ' + np.__version__,
'\nPillow>>Image: ' + Image.__version__)
print('\nTraining Initialized...')
start_time = time.time()
#Creatung directories
createFolder('./Model/')
#recognizer = cv2.face.createLBPHFaceRecognizer()
#recognizer = cv2.face.LBPHFaceRecognizer_create()
#OpenCv: 4.1.2
recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
def getImagesAndLabels(path):
imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
#empty lists for storing Lables and features
faceSamples = []
Ids = []
for imagePath in imagePaths:
pilImage = Image.open(imagePath).convert('L')
imageNp = np.array(pilImage, 'uint8')
Id = int(os.path.split(imagePath)[-1].split(".")[1])
faces = detector.detectMultiScale(imageNp)
for (x, y, w, h) in faces:
faceSamples.append(imageNp[y:y + h, x:x + w])
Ids.append(Id)
return faceSamples, Ids
start_time = time.time()
faces, Ids = getImagesAndLabels('./EmployeeDetails/dataSet')
#training model on dataSet
recognizer.train(faces, np.array(Ids))
#trainer.yml stored in the folder trainer
recognizer.save('Model/model.yml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('Model/model.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
print("----Training Done in : %s seconds----" % (time.time() - start_time))
def createadmin(AdminId, AdminUserName, AdminPhoneNumber, AdminEmailId,
AdminPassword):
createFolder('./AdminDetails')
try:
if os.path.exists('./AdminDetails/admin_details.csv'):
print('Details directory already exists')
else:
print("Details directory doesn't Exist")
with open('./AdminDetails/admin_details.csv', 'w') as file:
writer = csv.writer(file)
writer.writerow([
"AdminIds", "AdminUserNames", "AdminPhoneNumbers",
"AdminEmailIds", "AdminPasswords"
])
print("Creating new directory for employee_details.csv.")
except OSError:
print("File Already Exists")
AdminId = int(AdminId)
AdminUserName = AdminUserName
AdminPhoneNumber = AdminPhoneNumber
AdminEmailId = AdminEmailId
AdminPassword = AdminPassword
df = pd.read_csv('./AdminDetails/admin_details.csv')
if int(AdminId) in df['AdminIds'].values:
print("\nAdmin already exists!!!")
print("\nExiting.")
else:
print("\nCreating New Admin.")
data = [{
'AdminIds': AdminId,
'AdminUserNames': AdminUserName,
'AdminPhoneNumbers': AdminPhoneNumber,
'AdminEmailIds': AdminEmailId,
'AdminPasswords': AdminPassword
}]
df = pd.read_csv('./AdminDetails/admin_details.csv')
df = df.append(data, ignore_index=True, sort=False)
df.to_csv('./AdminDetails/admin_details.csv', index=False)
upload_to_database()
def main():
ourClasses, youtubeClasses, youtubeClassesID, labelsTF = getClasses(
'classes.csv', "data/ontology.json", 'data/class_labels_indices.csv')
# ourClasses = [ourClasses[3]]
# youtubeClasses = [youtubeClasses[3]]
# youtubeClassesID = [youtubeClassesID[3]]
# labelsTF = [labelsTF[3]]
#Print to check
for i in range(0, len(ourClasses)):
print("Under {}".format(ourClasses[i]))
print(youtubeClasses[i])
print(youtubeClassesID[i])
print(labelsTF[i])
#Create all the folders!!!
createFolder("data/test_rawAudio")
createFolder("data/train_rawAudio")
for c in ourClasses:
createFolder("data/test_rawAudio/" + c)
createFolder("data/train_rawAudio/" + c)
#Download the raw train set
print("====Downloading Train Data====")
downloadYoutubeCSV("data/unbalanced_train_segments.csv",
"data/temp_train4.mp3",
"data/train_rawAudio/",
ourClasses,
youtubeClassesID,
startRow=500000)
return
#Download the raw test set
print("====Downloading Test Data====")
downloadYoutubeCSV("data/eval_segments.csv", "data/temp_test.mp3",
"data/test_rawAudio/", ourClasses, youtubeClassesID)
def collector(Id, UserName, PhoneNumber, EmailId):
#created folder for saving dataset images of user
createFolder('./EmployeeDetails/dataSet')
#creating employee_details
try:
if os.path.exists('./EmployeeDetails/employee_details.csv'):
print('Details directory already exists')
else:
print("Details directory doesn't Exist")
with open('./EmployeeDetails/employee_details.csv', 'w') as file:
writer = csv.writer(file)
writer.writerow(
["Ids", "UserNames", "PhoneNumbers", "EmailIds"])
print("Creating new directory for employee_details.csv.")
except OSError:
print("File Already Exists")
cam = cv2.VideoCapture(0)
detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
print("\n")
Id = int(Id)
UserName = UserName
PhoneNumber = PhoneNumber
EmailId = EmailId
df = pd.read_csv('./EmployeeDetails/employee_details.csv')
if int(Id) in df.values:
print("\nEmployee already exists!!!")
print("\nExiting.")
else:
print("\nCreating New User.")
data = [{
'Ids': Id,
'UserNames': UserName,
'PhoneNumbers': PhoneNumber,
'EmailIds': EmailId
}]
df = pd.read_csv('./EmployeeDetails/employee_details.csv')
df = df.append(data, ignore_index=True, sort=False)
df.to_csv('./EmployeeDetails/employee_details.csv', index=False)
df.drop(labels=['PhoneNumbers', 'UserNames'], axis=1, inplace=True)
df = df.rename(columns={"Ids": "Passwords"})
df.to_csv('./EmployeeDetails/employee_access_details.csv', index=False)
sampleNum = 0
while True:
ret, img = cam.read()
ret, img1 = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = detector.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 2)
#incrementing sample number
sampleNum = sampleNum + 1
sampleNum1 = str(sampleNum)
text = sampleNum
#saving the captured face in the dataset folder
cv2.imwrite(
"EmployeeDetails/dataSet/User." + str(Id) + '.' +
UserName + '.' + str(sampleNum) + '.' + ".jpg",
gray[y:y + h, x:x + w])
cv2.putText(img1, sampleNum1, (70, 150),
cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 3)
cv2.imshow('Scans', img1)
if cv2.waitKey(1) == 27:
break
# break if the sample number is morethan 20
elif sampleNum > 99:
break
cam.release()
cv2.destroyAllWindows()
print("----Done----")
import os
import pandas as pd
import csv
import numpy as np
from datetime import datetime
from functions import createFolder, upload_to_database
#creating hierarchy of directories as Attendance/Year/Month/Day
print("--Creating Main Attendance Directory.--")
createFolder('./Attendance/main_attendance')
#DateTime,TimeStamp,WeekDay Variable
now = datetime.now()
year_dir = str(now.year)
month_dir = str(now.month)
if len(month_dir) == 2:
pass
else:
month_dir = '0' + str(now.month)
day_dir = str(now.day)
if len(day_dir) == 2:
pass
else:
day_dir = '0' + str(now.day)
weekDays = ("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday",
"Sunday")
weekday = str(weekDays[now.weekday()])
import os
import cv2
import numpy as np
from PIL import Image
import time
from functions import createFolder
print('\nModule Versions: ')
print('OpenCv: ' + cv2.__version__, '\nNumpy: ' + np.__version__,
'\nPillow>>Image: ' + Image.__version__)
print('\nTraining Initialized...')
start_time = time.time()
#Creatung directories
createFolder('./Model/')
#recognizer = cv2.face.createLBPHFaceRecognizer()
#recognizer = cv2.face.LBPHFaceRecognizer_create()
#OpenCv: 4.1.2
recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
def getImagesAndLabels(path):
imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
#empty lists for storing Lables and features
faceSamples = []
Ids = []
for imagePath in imagePaths:
def directory():
#creating hierarchy of directories as Attendance/Year/Month/Day
print("--Creating Main Attendance Directory.--")
createFolder('./Attendance/main_attendance')
#DateTime,TimeStamp,WeekDay Variable
now = datetime.now()
year_dir = str(now.year)
month_dir = str(now.month)
if len(month_dir) == 2:
pass
else:
month_dir = '0' + str(now.month)
day_dir = str(now.day)
if len(day_dir) == 2:
pass
else:
day_dir = '0' + str(now.day)
weekDays = ("Monday", "Tuesday", "Wednesday", "Thursday", "Friday",
"Saturday", "Sunday")
weekday = str(weekDays[now.weekday()])
today_path = './Attendance/main_attendance/' + year_dir + '/' + month_dir
createFolder(today_path)
date_string = year_dir + '-' + month_dir + '-' + day_dir
filename = date_string + '_' + weekday
#student details csv
student_csv_path = './EmployeeDetails/employee_details.csv'
#adding more columns to students csv and saving the sheet for main_attendance
main_attendance_csv_path = today_path + '/' + filename + '.csv'
df = pd.read_csv(student_csv_path)
df["Attendance"] = 'Absent'
df["Attend_DateTime"] = int(0)
df["Attend_TimeStamp"] = float(0.0)
df["Leave_DateTime"] = int(0)
df["Leave_TimeStamp"] = float(0.0)
df.to_csv(main_attendance_csv_path, index=False)
print('--csv file created for main attendance--')
#creating csv and directory for
if os.path.exists('./Attendance/employee_attendance'):
for i in range(0, len(df)):
student_csv_path = './Attendance/employee_attendance/' + str(
df.iloc[i][0]) + '_' + df.iloc[i][1] + '.csv'
if os.path.exists(student_csv_path):
pass
else:
data = [
'Name', 'Date', 'Day', 'Attendance', 'Attend_DateTime',
'Attend_TimeStamp', 'Leave_DateTime', 'Leave_TimeStamp'
]
df1 = pd.DataFrame(columns=data)
df1.to_csv(student_csv_path, index=False)
print('--csv file created for: ' + df.iloc[i][1] + '--')
else:
createFolder('./Attendance/employee_attendance')
print("--Created Student Attendance Directory--")
data = [
'Name', 'Date', 'Day', 'Attendance', 'Attend_DateTime',
'Attend_TimeStamp', 'Leave_DateTime', 'Leave_TimeStamp'
]
for i in range(0, len(df)):
student_csv_path = './Attendance/employee_attendance/' + str(
df.iloc[i][0]) + '_' + df.iloc[i][1] + '.csv'
df1 = pd.DataFrame(columns=data)
df1.to_csv(student_csv_path, index=False)
print('--csv file created for: ' + df.iloc[i][1] + '--')
print('\n-----DONE-----')
main_attendance_database()
employee_attendance_database()
#################################################################################
### 700hP - Temp - RH
fct.plt_700_humidity(fnx, fnx.geopotential_pl.sel(pressure = 700.,
x = slice(lower_x, upper_x),
y = slice(lower_y, upper_y)).isel(time=int(forecast_in_hours))/100,
fnx.air_temperature_pl.sel(pressure = 700.,
x = slice(lower_x, upper_x),
y = slice(lower_y, upper_y)).isel(time = int(forecast_in_hours)) - 273.15,
fnx.relative_humidity_pl.sel(pressure = 700.,
x = slice(lower_x, upper_x),
y = slice(lower_y, upper_y)).isel(time = int(forecast_in_hours))*100,
andenes_x, andenes_y)
if savefig == 1:
fct.createFolder('%s/700hPa_RH_T/%s/' %(figdir,map_area))
plt.savefig('%s/700hPa_RH_T/%s/%s' %(figdir, map_area, fig_name), format = form, bbox_inches='tight', transparent=True)
print('plot saved: %s/700hPa_RH_T/%s/%s' %(figdir, map_area, fig_name))
plt.close()
#################################################################################
# convert Geopotential to height
# https://en.wikipedia.org/wiki/Geopotential
a = 6.378*10**6 # average radius of the earth [m]
G = 6.673*10**(-11) # gravitational constant [Nm2/kg2]
ma = 5.975*10**24 # mass of the earth [kg]
Z_1000 = (-a**2 * fnx.geopotential_pl.sel(pressure = 1000.,).isel(time = int(forecast_in_hours)))/\
(a * fnx.geopotential_pl.sel(pressure = 1000.,).isel(time = int(forecast_in_hours)) - G * ma)
# -*- coding: utf-8 -*-
"""
Created on Thu May 2 19:19:15 2019
@author: Omkar Shidore
https://www.github.com/OmkarShidore
"""
import cv2
import os
import pandas as pd
import csv
from functions import createFolder
#created folder for saving dataset images of user
createFolder('./EmployeeDetails/dataSet')
#creating employee_details
try:
if os.path.exists('./EmployeeDetails/employee_details.csv'):
print('Details directory already exists')
else:
print("Details directory doesn't Exist")
with open('./EmployeeDetails/employee_details.csv', 'w') as file:
writer = csv.writer(file)
writer.writerow(["Ids", "UserNames", "PhoneNumbers", "EmailIds"])
print("Creating new directory for employee_details.csv.")
except OSError:
print("File Already Exists")
cam = cv2.VideoCapture(0)
detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')