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import numpy as np
from django.shortcuts import render, redirect
from django.db.models import Count
from .models import *
import matplotlib.pyplot as plt
# Create your views here.
def home(request):
return render(request, 'index.html')
def alogin(request):
return render(request, 'admin.html')
def ulogin(request):
return render(request, 'user.html')
def usrreg(request):
return render(request, 'signup.html')
def signupaction(request):
email = request.POST['mail']
pwd = request.POST['pwd']
zip = request.POST['zip']
name = request.POST['name']
age = request.POST['age']
gen = request.POST['gen']
d1 = user.objects.filter(email__exact=email).count()
if d1 > 0:
return render(request, 'signup.html', {'msg': "Email ALSTMeady Registered"})
else:
d = user(name=name, email=email, pwd=pwd, zip=zip, gender=gen, age=age)
d.save()
return render(request, 'signup.html', {'msg': "Register Success, You can Login.."})
return render(request, 'signup.html', {'msg': "Register Success, You can Login.."})
def uloginaction(request):
if request.method == 'POST':
uid = request.POST['mail']
pwd = request.POST['pwd']
d = user.objects.filter(email__exact=uid).filter(pwd__exact=pwd).count()
if d > 0:
d = user.objects.filter(email__exact=uid)
request.session['email'] = uid
request.session['name'] = d[0].name
return render(request, 'user_home.html', {'data': d[0]})
else:
return render(request, 'user.html', {'msg': "Login Fail"})
else:
return render(request, 'user.html')
def adminlogindef(request):
if request.method == 'POST':
uid = request.POST['uid']
pwd = request.POST['pwd']
if uid == 'admin' and pwd == 'admin':
request.session['adminid'] = 'admin'
return render(request, 'admin_home.html')
else:
return render(request, 'admin.html', {'msg': "Login Fail"})
else:
return render(request, 'admin.html')
def uhome(request):
if "email" in request.session:
uid = request.session["email"]
d = user.objects.filter(email__exact=uid)
return render(request, 'user_home.html', {'data': d[0]})
else:
return render(request, 'user.html')
def ulogout(request):
try:
del request.session['email']
except:
pass
return render(request, 'user.html')
def adminhome(request):
if "adminid" in request.session:
return render(request, 'admin_home.html')
else:
return render(request, 'user.html')
def trainingpage(request):
return render(request, 'trainingpage.html')
def cnn(request):
from .Train_CNN import dl_evaluation_process
acc, precsn, recall, f1score=dl_evaluation_process()
d=accuracysc.objects.filter(algo='CNN')
d.delete()
d=accuracysc(algo='CNN', accuracyv=acc, prec=precsn, recall=recall, f1sc=f1score)
d.save()
return render(request, 'trainingpage.html', {'msg': "CNN Classifier Training & Testing Completed Successfully"})
def ann(request):
from .Train_ANN import dl_evaluation_process
acc, precsn, recall, f1score=dl_evaluation_process()
d=accuracysc.objects.filter(algo='ANN')
d.delete()
d=accuracysc(algo='ANN', accuracyv=acc, prec=precsn, recall=recall, f1sc=f1score)
d.save()
return render(request, 'trainingpage.html', {'msg': "ANN Classifier Training & Testing Completed Successfully"})
def lstm(request):
from .Train_LSTM import dl_evaluation_process
acc, precsn, recall, f1score=dl_evaluation_process()
d=accuracysc.objects.filter(algo='LSTM')
d.delete()
d=accuracysc(algo='LSTM', accuracyv=acc, prec=precsn, recall=recall, f1sc=f1score)
d.save()
return render(request, 'trainingpage.html', {'msg': "LSTM Classifier Training & Testing Completed Successfully"})
def accuracyview(request):
if "adminid" in request.session:
d = accuracysc.objects.all()
accuracygraph()
precgraph()
recallgraph()
f1graph()
return render(request, 'viewaccuracy.html', {'data': d})
else:
return render(request, 'admin.html')
def viewgraphs(request):
if "adminid" in request.session:
accuracygraph()
precgraph()
recallgraph()
f1graph()
return render(request, 'viewgraph.html')
else:
return render(request, 'admin.html')
def accuracygraph():
if True:
data = {}
row = accuracysc.objects.filter(algo='CNN')
rlist = []
for r in row:
rlist.append(r.accuracyv)
data['CNN']=rlist
row = accuracysc.objects.filter(algo='ANN')
rlist = []
for r in row:
rlist.append(r.accuracyv)
data['ANN']=rlist
row = accuracysc.objects.filter(algo='LSTM')
rlist = []
for r in row:
rlist.append(r.accuracyv)
data['LSTM']=rlist
from .bargraph import bargraph
bargraph.view(data,'acc.jpg', 'Accuracy')
def precgraph():
if True:
data = {}
row = accuracysc.objects.filter(algo='CNN')
rlist = []
for r in row:
rlist.append(r.prec)
data['CNN']=rlist
row = accuracysc.objects.filter(algo='LSTM')
rlist = []
for r in row:
rlist.append(r.prec)
data['LSTM']=rlist
row = accuracysc.objects.filter(algo='ANN')
rlist = []
for r in row:
rlist.append(r.prec)
data['ANN']=rlist
from .bargraph import bargraph
bargraph.view(data,'prec.jpg', 'Precision')
def recallgraph():
if True:
data = {}
row = accuracysc.objects.filter(algo='CNN')
rlist = []
for r in row:
rlist.append(r.recall)
data['CNN']=rlist
row = accuracysc.objects.filter(algo='LSTM')
rlist = []
for r in row:
rlist.append(r.recall)
data['LSTM']=rlist
row = accuracysc.objects.filter(algo='ANN')
rlist = []
for r in row:
rlist.append(r.recall)
data['ANN']=rlist
from .bargraph import bargraph
bargraph.view(data,'recall.jpg', 'Recall')
def f1graph():
if True:
data = {}
row = accuracysc.objects.filter(algo='CNN')
rlist = []
for r in row:
rlist.append(r.f1sc)
data['CNN']=rlist
row = accuracysc.objects.filter(algo='LSTM')
rlist = []
for r in row:
rlist.append(r.f1sc)
data['LSTM']=rlist
row = accuracysc.objects.filter(algo='ANN')
rlist = []
for r in row:
rlist.append(r.f1sc)
data['ANN']=rlist
from .bargraph import bargraph
bargraph.view(data,'f1sc.jpg', 'F1 Score')
def search(request):
import sys,tweepy,re
if request.method=='POST':
keys=request.POST['keys']
from .TweetSearch import TweetSearch
l=TweetSearch.search(keys)
print(l,'><<<<<<<<<<<<<<<<<<<<<<<<')
ii=1
from .LSTM import get_predictions
res=get_predictions(l)
print("res=",res)
t=tweets.objects.all()
t.delete()
print(l)
for l1 in range(len(res)):
try:
r=tweets(sno=ii,tweet=l[l1], sentiment=res[l1])
r.save()
except:
pass
ii=ii+1
data=tweets.objects.all()
print("data=",data)
return render(request, 'tweetsresults.html',{'data':data})
else:
return render(request, 'search.html')
def sentiresults(request):
from .Freq import CountFrequency
from .Graphs import viewg
senti=[]
if "email" in request.session:
data=tweets.objects.all()
for d1 in data:
senti.append(d1.sentiment)
d=CountFrequency(senti)
viewg(d)
return render(request, 'tweetsresults2.html',{'data':data})
else:
return render(request, 'user.html')
def viewgraph2(request):
if "email" in request.session:
from PIL import Image
im = Image.open(r"g1.jpg")
im.show()
return redirect('sentiresults')
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