app.py

from flask import Flask, request, render_template,  redirect, session
import os
from PIL import Image
import numpy as np
import tensorflow as tf
import pandas as pd




app = Flask(__name__)

global last_uploaded_image_path
last_uploaded_image_path = None


# Set the upload folder and allowed extensions
app.config['UPLOAD_FOLDER'] = 'uploads'
app.config['ALLOWED_EXTENSIONS'] = {'png', 'jpg', 'jpeg', 'gif'}

# Check if the file extension is allowed
def allowed_file(filename):
    return '.' in filename and filename.rsplit('.', 1)[1].lower() in app.config['ALLOWED_EXTENSIONS']

def dataset(user_input):
    d = pd.read_csv('data.csv')

    data = {}
    recom = {}
    data['image'] = f"../static/img/{list(d[d['name'] == user_input]['image'])[0]}"
    data['water'] = list(d[d['name'] == user_input]['water'])[0]
    data['blue'] = list(d[d['name'] == user_input]['blue'])[0]
    data['green'] = list(d[d['name'] == user_input]['green'])[0]
    data['grey'] = list(d[d['name'] == user_input]['grey'])[0]
    data['serving_size'] = list(d[d['name'] == user_input]['serving_size'])[0]
    data['name'] = user_input.title()
    if list(d[d['name'] == user_input]['recommendation'])[0] == 1:
        user_input = list(d[d['name'] == user_input]['recommendation_name'])[0]
        recom['image'] = f"../static/img/{list(d[d['name'] == user_input]['image'])[0]}"
        recom['water'] = list(d[d['name'] == user_input]['water'])[0]
        recom['blue'] = list(d[d['name'] == user_input]['blue'])[0]
        recom['green'] = list(d[d['name'] == user_input]['green'])[0]
        recom['grey'] = list(d[d['name'] == user_input]['grey'])[0]
        recom['serving_size'] = list(d[d['name'] == user_input]['serving_size'])[0]
        recom['name'] = user_input.title()
        
        return [data, recom]
    return [data]

def login_authentication(username, password):
    d = pd.read_csv("user_login_data.csv")
    p = d[d['username'] == username]['password'][0]
    if str(p) == password:
        return "Yes"
    return "No"

def signp_data(username, password):
    d = pd.read_csv('user_login_data.csv')
    new_data = pd.DataFrame({
    'username': username,
    'password': password,
    }, index=[0])
    appended_data = pd.concat([d, new_data], ignore_index=True)
    appended_data.to_csv('user_login_data.csv', index=False)



@app.route('/')
def index():
    return render_template('index.html')

@app.route('/login', methods=['POST'])
def loginpage():
    return render_template('login.html')

@app.route('/login_data', methods=['POST'])
def login():
    if request.method == 'POST':
        username = request.form['username']
        password = request.form['password']
        print(username, password)
        print(login_authentication(username=username.strip(), password=password))
        if login_authentication(username=username.strip(), password=password) == "Yes":
            return render_template("index.html")
        return "<h1>User not login, Please sign up first</h1>"

@app.route('/signup', methods=['POST'])
def signup():
    if request.method == 'POST':
        username = request.form['username']
        password1 = request.form['password1']
        password2 = request.form['password2']
        if password1 == password2:
            signp_data(username=username, password=password1)
            
            return render_template("index.html")
        return "<h1>Passwords are not same</h1>"
    



@app.route('/dashboard', methods=['POST'])
def dashboard():
    return render_template('dashboard.html')


@app.route('/search', methods=['POST'])
def search_page():
    return render_template('search.html')



@app.route('/search_object', methods=['POST'])
def process_form():
    if request.method == 'POST':
        user_input = request.form['objectname']
        user_input = user_input.lower().strip()
        print(user_input)
        result = dataset(user_input)
        print(result)
        if len(result) == 1:
            return render_template('object.html', result=result[0])
        return render_template('objectWithRecom.html', result=result[0], recom=result[1])
    return "Error"

@app.route('/upload', methods=['POST'])
def upload_page1():
    return render_template('upload.html')



@app.route('/process_image', methods=['POST'])
def process_image():
    if 'image' not in request.files:
        return "No file part"
    
    file = request.files['image']

    if file.filename == '':
        return "No selected file"
    if file and allowed_file(file.filename):
        if not os.path.exists(app.config['UPLOAD_FOLDER']):
            os.makedirs(app.config['UPLOAD_FOLDER'])
        file_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
        file.save(file_path)

        # Store the file path in the global variable
        last_uploaded_image_path = file_path

        img=tf.keras.preprocessing.image.load_img(last_uploaded_image_path ,target_size=(224,224))

        model = tf.keras.models.load_model('Toothpaste_Toothbrush_Apple_Banana_Grape_V2.h5')

        x=tf.keras.preprocessing.image.img_to_array(img)
        x = np.expand_dims(x, axis=0)  # Add a batch dimension
        x = x / 255.0
        result = np.argmax(model.predict(x), axis=1)
        if result[0] == 0:
            user_in = 'apple'
        elif result[0] == 1:
            user_in = 'banana'
        elif result[0] == 2:
            user_in = 'grape'
        elif result[0] == 3:
            user_in = 'toothbrush'
        elif result[0] == 4:
            user_in = 'toothpaste'
        print(user_in)
        data = dataset(user_in)
        print(data)
        if len(data) == 1:
            return render_template('object.html', result=data[0])
        return render_template('objectWithRecom.html', result=data[0], recom=data[1])
    

if __name__ == '__main__':
    app.run(host="0.0.0.0")