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x_train=x_train.astype('float32') | |
x_test=x_test.astype('float32') | |
#intializing callbacks | |
early_stopping=keras.callbacks.EarlyStopping(patience=15,restore_best_weights=True) | |
model1.compile(optimizer='Adam',loss='categorical_crossentropy',metrics=['accuracy']) | |
model1.fit(x_train,y_train, | |
batch_size=64, |
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fer_json = model1.to_json() | |
with open("fer.json", "w") as json_file: | |
json_file.write(fer_json) | |
model1.save_weights("fer.h5") |
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flask | |
tensorflow | |
opencv-python | |
numpy |
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from flask import Flask, render_template, Response | |
import cv2 | |
import numpy as np | |
from tensorflow.keras.models import model_from_json | |
from tensorflow.keras.preprocessing import image |
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model = model_from_json(open("fer.json", "r").read()) #load model | |
model.load_weights('fer.h5') #load weights | |
face_haar_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') | |
camera = cv2.VideoCapture(0) | |
app = Flask(__name__) |
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import smtplib, ssl | |
import bs4,webbrowser | |
import requests |
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def getLink(number): | |
link='https://www.google.com/search?q='+'geeksforgeeks puzzle '+number | |
response=requests.get(link) | |
ls=[] | |
links=[] | |
try: | |
soup=bs4.BeautifulSoup(response.text,features="html.parser") | |
for tag in soup.find_all('a'): |
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def sendMail(): | |
smtp_server = "smtp.gmail.com" | |
port = 587 # For starttls | |
sender_email = "sender-mail-id" #sender's mail id | |
receiver_email = ['reciever-mail-id'] #list of reciever's mail ids | |
#password = getpass.getpass(prompt="Type your password and press enter: ") | |
password = "enter-your-password-here" | |
print('Runnning\n') | |
file1 = open("data.txt","r") |
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from apscheduler.schedulers.blocking import BlockingScheduler | |
from run import sendMail | |
sched = BlockingScheduler() | |
@sched.scheduled_job('cron', day_of_week='mon-fri', hour=8) | |
def scheduled_job(): | |
print('This job is run every weekday at 8 AM.') | |
sendMail() | |
sched.start() |
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clock: python clock.py |