app.py

# Importing necessary modules
from flask import Flask,render_template,request,flash,redirect,url_for,g,session,Response
import random
import torch
import json
from src.model import NeuralNet
from src.basics import bag_of_words, tokenize, stem
from src.nearby import hospital_search,pharmacy_search
import pymongo
from pymongo import MongoClient
from flask_login import login_user,current_user
import time
from datetime import datetime
from datetime import date
from src.camera import VideoCamera
import numpy as np
import face_recognition as fr
import cv2
from decouple import config


#connecting to out MongoDB Database using decouple

app=Flask(__name__)
app.secret_key=config('secretLeMedicin')
client=MongoClient(config('LeMedicinMongo'))
db=client['Patient']
data=db.Prescriptions

# app route for login/register pages
@app.route("/")
def login():    
    if g.user:
        return redirect(url_for('test'))    
    return render_template('login.html')

@app.route("/register")
def reg():
    return render_template('register.html')

@app.route('/face_login')
def index():
    # rendering webpage
    return render_template('face.html')

# get the live feed from webcam
def gen(camera):
    while True:
        #get camera frame
        frame = camera.get_frame()
        yield (b'--frame\r\n'
               b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')

@app.route('/video_feed')
def video_feed():
    return Response(gen(VideoCamera()),
                    mimetype='multipart/x-mixed-replace; boundary=frame')


# face recognition based login
def capture():    
    video = cv2.VideoCapture(0)
    face_cascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
    ret, frame = video.read()
    face_rects=face_cascade.detectMultiScale(frame,1.3,5)

    my_image = fr.load_image_file("Images/2.jpg")
    my_face_encoding = fr.face_encodings(my_image)[0]

    known_face_encondings = [my_face_encoding]
    known_face_names = ["SD"]       

    rgb_frame = frame[:, :, ::-1]

    face_locations = fr.face_locations(rgb_frame)
    face_encodings = fr.face_encodings(rgb_frame, face_locations)

    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):

        matches = fr.compare_faces(known_face_encondings, face_encoding)

        name = "Unknown"

        face_distances = fr.face_distance(known_face_encondings, face_encoding)

        best_match_index = np.argmin(face_distances)

        if matches[best_match_index]:
            name = known_face_names[best_match_index]
            return True
    
        
    return False

#  route for setting up the sessions if creditials/face matches
@app.route('/get_p')
def click():
    res=capture()
    if res==True:
        session['user']="s@s.com"
        return redirect(url_for('test'))
    else:
        flash("Face doesn't match/Not detected. Try Again")
        return render_template("face.html")

# login validations for patient and doctor login
@app.route("/d",methods=['POST'])
def doctor():
    email_d=None
    pass_d=None
    email_d=request.form.get('doctor_email')
    pass_d=request.form.get('doctor_pass')
    if email_d=='d@d.com' and pass_d=='12345':
        return redirect(url_for('doctor_home'))
    elif email_d is None or pass_d is None:
        flash("Please fill in both the fields")
        return render_template('login.html',user="d")
    else:
        flash("Invalid Credentials for Doctor Login")
        return render_template('login.html',user="d")
    
    return render_template('login.html')

@app.route("/p",methods=['POST'])
def patient():
    session.pop('user',None)
    email_p=None
    pass_p=None
    email_p=request.form.get('patient_email')
    pass_p=request.form.get('patient_pass')
    if email_p=='s@s.com' and pass_p=='12345':
        session['user']=email_p
        return redirect(url_for('test'))
    elif email_p is None or pass_p is None:
        flash("Please fill in both the fields")
        return render_template('login.html',user="p")
    elif email_p!='s@s.com' or pass_p!='12345':
        flash("Invalid credentials for Patient Login")
        return render_template('login.html',user="p")
    
    return render_template('login.html')
        


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

@app.route("/doctor_vc",methods=['GET','POST'])
def doc_vc():
    if request.method=='POST':
        illness=request.form.get('details')
        med=request.form.get('Med')
        qnty=request.form.get('qnty')
        name="Dr P.Gandhi"
        today = date.today()
        date1=today.strftime("%d/%m/%Y")
        doc={'Doctor':name,
        'Illness':illness,
        'Medicine':med,
        'Quantity':qnty,
        'date':date1}
        data.insert_one(doc)
        return redirect(url_for('doctor_home'))  

    return render_template('doctor_vc.html')
    
# features of the web app
@app.route("/tests")
def test():
    if g.user:
        return render_template('patient_home.html')
    flash("Please login before continuing")
    return render_template('login.html',user='g') 


@app.route("/tests/chatbot")
def chat():
    if g.user:
        return render_template("Chatbot_temp.html")
    flash("Please login before continuing")
    return render_template('login.html',user='g') 

@app.route("/tests/chatbot_get",methods=['GET'])
def chatbot():
    device=torch.device('cuda' if torch.cuda.is_available() else 'cpu')

    with open('intents.json','r') as f:
        intents=json.load(f)        
    FILE="src/data.pth"
    data=torch.load(FILE)
    input_size = data["input_size"]
    hidden_size = data["hidden_size"]
    output_size = data["output_size"]
    all_words = data['all_words']
    tags = data['tags']
    model_state = data["model_state"]

    model = NeuralNet(input_size, hidden_size, output_size).to(device)
    model.load_state_dict(model_state)
    model.eval()
   
    sentence = request.args.get("msg") #get data from input,we write js  to index.html
    sentence=tokenize(sentence)
    X=bag_of_words(sentence,all_words)
    X=X.reshape(1,X.shape[0])
    X=torch.from_numpy(X)
    output=model(X)
    _,predicted=torch.max(output,dim=1)
    tag=tags[predicted.item()]
    bot="I do not know...try something different😊"
    probs = torch.softmax(output, dim=1)
    prob = probs[0][predicted.item()]
    #print(prob.item())
    if prob.item() < 0.8:
        bot="I do not know...try something different😊"
        
    
    elif prob.item() >=0.8:
        for intent in intents['intents']:
            if tag == intent["tag"]:
                bot=random.choice(intent['responses'])      
        
        
    return bot

    

@app.route("/tests/self_assess",methods=['GET','POST'])
def self_assess():
    if g.user:
        if request.method=='POST':
            score=50
            fear=request.form.get('fear')
            eat=request.form.get('eat')
            confidence=request.form.get('confidence')
            future=request.form.get('future')
            relation=request.form.get('relation')
            activity=request.form.get('activity')
            score=score+int(fear)+int(eat)+int(confidence)+int(future)+int(relation)+int(activity)
            mssg=""
            if score>50 and score<100:
                mssg="Great, make your days even better!"
            elif score>100:
                mssg="Awesome, thats the motivation we need!"
            elif score<50 and score>0:
                mssg="Try to stay motiavted always. We would recommend you to consult Dr A."            
            elif score<0:
                mssg="Its highly important for you to consult Dr A, before something big happens."
            
            flash(mssg)
            return render_template('self-assessment2.html')
        return render_template('self-assessment2.html')
    
    flash("Please login before continuing")
    return render_template('login.html',user='g') 

@app.route("/tests/inkblot",methods=['GET','POST'])
def inkblot():
    if g.user:
        if request.method=='POST':
            score=50
            fear=request.form.get('1')
            eat=request.form.get('2')
            confidence=request.form.get('3')
            future=request.form.get('4')
            relation=request.form.get('5')
            
            score=score+int(fear)+int(eat)+int(confidence)+int(future)+int(relation)
            mssg=""
            if score>=50 and score<100:
                mssg="Great, make your days even better!"
            elif score>=100:
                mssg="Awesome, thats the motivation we need!"
            elif score<50 and score>0:
                mssg="Try to stay motivated always. We would recommend you to consult a doctor."            
            elif score<=0:
                mssg="Its highly important for you to consult a doctor, before something big happens."
            
            flash(mssg)
            return render_template('inkblot.html')
        return render_template('inkblot.html')
    flash("Please login before continuing")
    return render_template('login.html',user='g') 


@app.route("/doctor_list")
def doctor_list():
    return render_template('doctor_info.html')


@app.route("/video_patient/<string:name>")
def v_p(name):
    if g.user:
        return render_template('video_chat.html',name=name)
    flash("Please login before continuing")
    return render_template('login.html',user='g') 


@app.route("/shop",methods=['GET','POST'])
def shop_search():
    if g.user:
        items=["A Tabs","B Tabs","C Tabs"]
        qnty=[10,18,5]
        price=[10,15,18]
        res=False
        if request.method=='POST':       
            search=request.form.get('search')
            for i in range(0,len(items)):
                if search.lower()==items[i].lower():
                    res=True
                    q=qnty[i]
                    p=price[i]
                    return render_template('shop2.html',res=res,q=q,p=p,item=search)
            
            return render_template('shop2.html',res=res)
        
        return render_template('shop.html')
    flash("Please login before continuing")
    return render_template('login.html',user='g') 


@app.route("/shop/confirmation")
def confirm():
    if g.user:
        return render_template('payment_ack.html')  
    flash("Please login before continuing")
    return render_template('login.html',user='g') 


@app.route("/prescription")
def pres():
    if g.user:            
        return render_template('prescription.html',p=data)  
    flash("Please login before continuing")
    return render_template('login.html',user='g')   

@app.route("/logout")
def logoute():
    if g.user:
        session.pop('user', None)
        return render_template('login.html')
    flash("Please login before continuing")
    return render_template('login.html')  

@app.route("/nearby",methods=['GET','POST'])
def neerby():
    if g.user:
        res=False
        if request.method=='POST':
            choice=request.form.get('choice')
            locality=request.form.get('locality')
            
            if choice=='Hospital':
                names=hospital_search(locality)
                res=True
                
            else:
                names=pharmacy_search(locality)
                res=True
                
            return render_template('hospital.html',res=res,names=names)        
            
        return render_template('hospital.html',res=res)
    
    flash("Please login before continuing")
    return render_template('login.html',user='g') 

# check if there's already an existing session 
@app.before_request
def before_request():
    g.user=None
    det=[]
    if 'user' in session:
        g.user=session['user']  
              
    
if __name__=="__main__":
    app.run(debug=True)