from django.shortcuts import render, HttpResponse

from .forms import UserRegistrationForm

from .models import UserRegistrationModel,UserImagePredictinModel

from django.contrib import messages

from django.core.files.storage import FileSystemStorage

from .utility.GetImageStressDetection import ImageExpressionDetect

from .utility.MyClassifier import KNNclassifier

from subprocess import Popen, PIPE

import subprocess

# Create your views here.

# Create your views here.

def UserRegisterActions(request):

    if request.method == 'POST':

        form = UserRegistrationForm(request.POST)

        if form.is_valid():

            print('Data is Valid')

            form.save()

            messages.success(request, 'You have been successfully registered')

            form = UserRegistrationForm()

            return render(request, 'UserRegistrations.html', {'form': form})

        else:

            messages.success(request, 'Email or Mobile Already Existed')

            print("Invalid form")

    else:

        form = UserRegistrationForm()

    return render(request, 'UserRegistrations.html', {'form': form})

def UserLoginCheck(request):

    if request.method == "POST":

        loginid = request.POST.get('loginname')

        pswd = request.POST.get('pswd')

        print("Login ID = ", loginid, ' Password = ', pswd)

        try:

            check = UserRegistrationModel.objects.get(loginid=loginid, password=pswd)

            status = check.status

            print('Status is = ', status)

            if status == "activated":

                request.session['id'] = check.id

                request.session['loggeduser'] = check.name

                request.session['loginid'] = loginid

                request.session['email'] = check.email

                print("User id At", check.id, status)

                return render(request, 'users/UserHome.html', {})

            else:

                messages.success(request, 'Your Account Not at activated')

                return render(request, 'UserLogin.html')

        except Exception as e:

            print('Exception is ', str(e))

            pass

        messages.success(request, 'Invalid Login id and password')

    return render(request, 'UserLogin.html', {})

def UserHome(request):

    return render(request, 'users/UserHome.html', {})

def UploadImageForm(request):

    loginid = request.session['loginid']

    data = UserImagePredictinModel.objects.filter(loginid=loginid)

    return render(request, 'users/UserImageUploadForm.html', {'data': data})

def UploadImageAction(request):

    image_file = request.FILES['file']

    # let's check if it is a csv file

    if not image_file.name.endswith('.jpg'):

        messages.error(request, 'THIS IS NOT A JPG  FILE')

    fs = FileSystemStorage()

    filename = fs.save(image_file.name, image_file)

    # detect_filename = fs.save(image_file.name, image_file)

    uploaded_file_url = fs.url(filename)

    obj = ImageExpressionDetect()

    emotion = obj.getExpression(filename)

    username = request.session['loggeduser']

    loginid = request.session['loginid']

    email = request.session['email']

    UserImagePredictinModel.objects.create(username=username,email=email,loginid=loginid,filename=filename,emotions=emotion,file=uploaded_file_url)

    data = UserImagePredictinModel.objects.filter(loginid=loginid)

    return render(request, 'users/UserImageUploadForm.html', {'data':data})

def UserEmotionsDetect(request):

    if request.method=='GET':

        imgname = request.GET.get('imgname')

        obj = ImageExpressionDetect()

        emotion = obj.getExpression(imgname)

        loginid = request.session['loginid']

        data = UserImagePredictinModel.objects.filter(loginid=loginid)

        return render(request, 'users/UserImageUploadForm.html', {'data': data})

def UserLiveCameDetect(request):

    obj = ImageExpressionDetect()

    obj.getLiveDetect()

    return render(request, 'users/UserLiveHome.html', {})

def UserKerasModel(request):

    # p = Popen(["python", "kerasmodel.py --mode display"], cwd='StressDetection', stdout=PIPE, stderr=PIPE)

    # out, err = p.communicate()

    subprocess.call("python kerasmodel.py --mode display")

    return render(request, 'users/UserLiveHome.html', {})

def UserKnnResults(request):

    obj = KNNclassifier()

    df,accuracy,classificationerror,sensitivity,Specificity,fsp,precision = obj.getKnnResults()

    df.rename(columns={'Target': 'Target', 'ECG(mV)': 'Time pressure', 'EMG(mV)': 'Interruption', 'Foot GSR(mV)': 'Stress', 'Hand GSR(mV)': 'Physical Demand', 'HR(bpm)': 'Performance', 'RESP(mV)': 'Frustration', }, inplace=True)

    data = df.to_html()

    return render(request,'users/UserKnnResults.html',{'data':data,'accuracy':accuracy,'classificationerror':classificationerror,

                                                       'sensitivity':sensitivity,"Specificity":Specificity,'fsp':fsp,'precision':precision})