GlassDetectorAndRecommender.py

from __future__ import division, print_function
# coding=utf-8
import sys
import os
import glob
import re, glob, os,cv2
import numpy as np
import pandas as pd
import glass_detection
from shutil import copyfile
import shutil
from distutils.dir_util import copy_tree

# Flask utils
from flask import Flask, redirect, url_for, request, render_template
from werkzeug.utils import secure_filename
from gevent.pywsgi import WSGIServer

# Define a flask app
app = Flask(__name__)

for f in os.listdir("static\\similar_images\\"):
    os.remove("static\\similar_images\\"+f)

print('Model loaded. Check http://127.0.0.1:5000/')


@app.route('/', methods=['GET'])
def index():
    # Main page
    return render_template('index.html')


@app.route('/predict', methods=['GET', 'POST'])
def upload():
    if request.method == 'POST':
        # Get the file from post request
        f = request.files['file']

        # Save the file to ./uploads
        basepath = os.path.dirname(__file__)
        file_path = os.path.join(
            basepath, 'uploads', secure_filename(f.filename))
        f.save(file_path)

        # Make prediction
        similar_glass_details=glass_detection.getUrl(file_path)


        print("Checking for similar images.......")
        #getting similar images
        test_image = cv2.imread(file_path) 
        gray_image = cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY) 
        histogram_test = cv2.calcHist([gray_image], [0],  
                                 None, [256], [0, 256])

        hist_dict={}
        for image in os.listdir("data\\Data\\"):
            try:
                img_to_compare = cv2.imread("data\\Data\\"+image) 
                img_to_compare = cv2.cvtColor(img_to_compare, cv2.COLOR_BGR2GRAY) 
                img_to_compare_hist = cv2.calcHist([img_to_compare], [0],  
                                         None, [256], [0, 256])
                c=0
                i = 0
                while i<len(histogram_test) and i<len(img_to_compare_hist): 
                    c+=(histogram_test[i]-img_to_compare_hist[i])**2
                    i+= 1
                c = c**(1 / 2)
                hist_dict[image]=c[0]
            except:
                print(image)
        sort_dict = sorted(hist_dict.items(), key=lambda x: x[1], reverse=False)[1:11]
        similar_images=[]
        for i in sort_dict:
            similar_images.append("data\\Data\\"+str(i[0]))

        for f in os.listdir("static\\similar_images\\"):
            if(f=="DetectedGlass1.jpg"):
                pass
            else:
                os.remove("static\\similar_images\\"+f)

        for count, image in enumerate(similar_images):
            dst=f"static\\similar_images\\"
            #copyfile(image, dst)
            shutil.copy(image, dst, follow_symlinks=True)

        for count, filename in enumerate(os.listdir("static\\similar_images")): 
            dst ="Glasses" + str(count+1) + ".jpg"
            src ="static\\similar_images\\"+ filename 
            dst ="static\\similar_images\\"+ dst 
            os.rename(src, dst) 

        return glass_details
    return None

if __name__ == '__main__':
    app.run(debug=False)