Search Engine.py

# -*- coding: utf-8 -*-
"""
Created on Sun Jun 20 08:03:07 2021

@author: tech crusaders
"""

import cv2 as cv
import matplotlib.image as img
import matplotlib.pyplot as plt
import csv
import numpy as np


#histogram feature vector
def rgb_histo(image):
 
    histo= cv.calcHist([image],[0],None,[256],[0,256])
    fv=np.array(histo)
    for i in range(1,3):
        histo= cv.calcHist([image],[i],None,[256],[0,256])
        fv=np.append(fv,histo,0)    
    return fv

#upload image in theproject folder before reading

print("Input name of the image to be searched: ")
name=input()+'.jpg'
q_img= img.imread(name)
plt.imshow(q_img)
plt.show()

q_vec=rgb_histo(q_img)

plt.plot(q_vec)
plt.show()
print(q_vec[0])

with open("Database.csv",'r') as csvfile:
     sim_im={}
     csvreader= csv.reader(csvfile)
     
     c_vec= next(csvreader)
     c_vec=[float(s[1:-1]) for s in c_vec]
     c_vec=np.array(c_vec)
     c_vec=c_vec.astype(np.float32)
     c_vec.shape=(768,1)
     
     p = cv.compareHist(c_vec, q_vec ,cv.HISTCMP_BHATTACHARYYA)
     q = cv.compareHist(q_vec, c_vec ,cv.HISTCMP_CORREL)
     
     
     if p<0.23 or q>0.88:
         sim_im[q]=c_vec
     for row in csvreader:
         
         c_vec=row
         c_vec=[float(s[1:-1]) for s in c_vec]
         c_vec=np.array(c_vec)
         c_vec=c_vec.astype(np.float32)
         c_vec.shape=(768,1)
         p = cv.compareHist(c_vec, q_vec ,cv.HISTCMP_BHATTACHARYYA)
         q = cv.compareHist(q_vec, c_vec ,cv.HISTCMP_CORREL)
     
     
         if p<0.238 or q>0.88:
             sim_im[q]=c_vec
         
csvfile.close()

#dictionary of similar images
print(sim_im.keys())