rahim42324

import requests
from bs4 import BeautifulSoup

rahim42324

import requests
from bs4 import BeauftifulSoup

url="https://www.zillow.com/homes/872-OLD-HICKORY-RD--PITTSBURGH,-PA-15243_rb/11659068_zpid/"

r=requests.get(ur)
print(r)

rahim42324

import requests
from bs4 import BeauftifulSoup

req_headers = {
        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
        'accept-encoding': 'gzip, deflate, br',
        'accept-language': 'en-US,en;q=0.8',
        'upgrade-insecure-requests': '1',
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Safari/537.36'
    }

rahim42324

import cv2

# colored Image

Img = cv2.imread ("image.png",1)
 
# Black and White (gray scale)

Img_1 = cv2.imread ("image.png",0)

rahim42324

import cv2

# colored Image
Img = cv2.imread ("image.png",1)
 
# Black and White (gray scale)
Img_1 = cv2.imread ("image.png",0)

rahim42324

import cv2
 
# Black and White (gray scale)
Img = cv2.imread ("image.png";,0)
cv2.imshow("image.png";, img)
cv2.waitKey(0)

# cv2.waitKey(2000)
cv2.destroyAllWindows()

rahim42324

Import cv2
 
# Black and White (gray scale)
 
Img = cv2.imread ("image.png",0)
 
print(img.shape)

rahim42324

import cv2
 
# Black and White (gray scale)
img = cv2.imread (“Penguins.jpg”,0)
 
resized_image = cv2.resize(img, (650,500))
 
cv2.imshow("image.png", resized_image)

cv2.waitKey(0)

rahim42324

import cv2 
import numpy as np 
  
image = cv2.imread('fruits.jpg') 
  
cv2.imshow('Original Image', image) 
cv2.waitKey(0) 
  
# Gaussian Blur 
Gaussian = cv2.GaussianBlur(image, (7, 7), 0) 

rahim42324

import cv2 
import numpy as np 
  
image = cv2.imread('C://Geeksforgeeks//image_processing//fruits.jpg') 
  
cv2.imshow('Original Image', image) 
cv2.waitKey(0) 
  
# Gaussian Blur 
Gaussian = cv2.GaussianBlur(image, (7, 7), 0)