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')