Abhayparashar31

from flask import Flask,render_template,request 
import pickle

###Loading model and cv
cv = pickle.load(open('cv.pkl','rb')) ##loading cv
model = pickle.load(open('spam.pkl','rb')) ##loading model

app = Flask(__name__) ## defining flask name

@app.route('/') ## home route

Abhayparashar31

for index, item in df.iterrows():
        #print(index,item['birthday'])
        bday = item['Birthday'].strftime("%d-%m") ##wishing time  from excel file
        #print(type(bday)) 
        if(bday == today) and yearnow not in str(item["Year"]):  ## birthday data ==  today date and birthday year is not equal to current year
            sendEmail(item['Email'] ,"Happy BIrthday "+item["Name"], item['message']) ## pass arguments to the send email funciton and call it
            update.append(index) ## update the index by one ## we need to check the whole records
    for i in update:
        yr = df.loc[i, 'Year'] ## update the year by one
        #print(yr)

Abhayparashar31

from bs4 import BeautifulSoup
import re
import requests
import heapq
from nltk.tokenize import sent_tokenize,word_tokenize
from nltk.corpus import stopwords

url = str(input("Paste the url"\n"))
num = int(input("Enter the Number of Sentence you want in the summary"))
num = int(num)

Abhayparashar31

# A single node of a singly linked list
class Node:
  # constructor
  def __init__(self, data = None, next=None): 
    self.data = data
    self.next = next

# A Linked List class with a single head node
class LinkedList:
  def __init__(self):  

Abhayparashar31

import face_recognition
import cv2
import os
from google.colab.patches import cv2_imshow
def read_img(path):
  img = cv2.imread(path)
  (h,w) = img.shape[:2]
  width = 500
  ratio = width / float(w)
  height = int(h * ratio)

Abhayparashar31

from flask import Flask,render_template,request
import pickle
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
import pickle

###Loading model and cv

Abhayparashar31

import cv2
img = cv2.imread("images/test.jpg")
imgCropped = img[50:283,25:190]
shape = imgCropped.shape
print(shape[0])
imgCropped = cv2.resize(imgCropped,(shape[0]*12//10,shape[1]*2))
cv2.imshow("Image cropped",imgCropped)
cv2.imshow("Image",img)
cv2.waitKey(0)

Abhayparashar31

    FONT_HERSHEY_SIMPLEX                  normal size sans-serif font
    FONT_HERSHEY_PLAIN                    small size sans-serif font
    FONT_HERSHEY_DUPLEX                   normal size sans-serif font (more complex than FONT_HERSHEY_SIMPLEX)
    FONT_HERSHEY_COMPLEX                  normal size serif font
    FONT_HERSHEY_TRIPLEX                  normal size serif font (more complex than FONT_HERSHEY_COMPLEX)
    FONT_HERSHEY_COMPLEX_SMALL            smaller version of FONT_HERSHEY_COMPLEX
    FONT_HERSHEY_SCRIPT_SIMPLEX           hand-writing style font
    FONT_HERSHEY_SCRIPT_COMPLEX           more complex variant of FONT_HERSHEY_SCRIPT_SIMPLEX
    FONT_ITALIC                           flag for italic font

Abhayparashar31

import cv2
import numpy as np
img = cv2.imread("images/img0.jpg")
cv2.line(img,(110,260),(300,260),(0,255,0),3)
cv2.rectangle(img,(300,280),(100,20),(0,0,255),2)
cv2.circle(img,(200,130),90,(255,255,0),2)
cv2.putText(img,"MONALISA",(120,250),cv2.FONT_HERSHEY_COMPLEX,1,(255,255,255),2)
cv2.imshow("Image",img)
cv2.waitKey(0)

Abhayparashar31

from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img

datagen = ImageDataGenerator(
        rotation_range=40,
        width_shift_range=0.2,
        height_shift_range=0.2,
        rescale=1./255,
        shear_range=0.2,
        zoom_range=0.4,
        horizontal_flip=True,