import pandas as pd
import mysql.connector
import time
import os
import cv2
import sys
from dotenv import load_dotenv
from datetime import timedelta
from datetime import datetime
from pathlib import Path
from importlib import reload
import logging
reload(logging)
import coloredlogs
import sqlalchemy
import telegram
import json, glob, os
from dotenv import load_dotenv





img1=cv2.imread("hiwar_tounsi/iframes/safiy_qalbak/2022-12-30_22_45_09.1672673355_3044_6.png")
img2=cv2.imread("hiwar_tounsi/iframe_live/index202301051672876523.1672876526_20_6.png")

sift = cv2.xfeatures2d.SIFT_create()
kp_1, desc_1 = sift.detectAndCompute(img1, None)
kp_2, desc_2 = sift.detectAndCompute(img2, None)

index_params = dict(algorithm=0, trees=5)
search_params = dict()
flann = cv2.FlannBasedMatcher(index_params, search_params)
matches = flann.knnMatch(desc_1, desc_2, k=2)

good_points = []
ratio = 0.2
for m, n in matches:
    if m.distance < ratio*n.distance:
        good_points.append(m)

print('len is ',len(good_points))

result = cv2.drawMatches(img1, kp_1, img2, kp_2, good_points, None)


cv2.imshow("result", result)
cv2.imshow("Original", img1)
cv2.imshow("Duplicate", img2)
cv2.waitKey(0)
cv2.destroyAllWindows()