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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') | |