from django.shortcuts import render
from image.models import fva
from PIL import Image
from PIL import ImageStat
from PIL import ImageFilter
from math import log
import mysql.connector

def homepage(request):
return render(request,'index.html',{})

def rootmeansquare( im_file ):
im = Image.open(im_file).convert('L')
stat = ImageStat.Stat(im)
return stat.rms[0]

def average( im_file ):
im = Image.open(im_file)
stat = ImageStat.Stat(im)
return stat.mean[0]

def varaince( im_file ):
im = Image.open(im_file)
stat = ImageStat.Stat(im)
return stat.var[0]

def standarddeviation( im_file ):
im = Image.open(im_file)
stat = ImageStat.Stat(im)
return stat.stddev[0]

def edgedetection( im_file ):
im = Image.open(im_file)
im = im.filter(ImageFilter.FIND_EDGES)
stat = ImageStat.Stat(im)
return stat.mean[0]

def histogramvalue( im_file):
im = Image.open(im_file)
hist=im.histogram()
sumhist=sum(hist)
lenhist=len(hist)
avghist=float(sumhist/lenhist)
return avghist

def entropy( im_file ):
img = Image.open(im_file)
histogram=img.histogram()
log2 = lambda x:log(x)/log(2)

total = len(histogram)
counts = {}
for item in histogram:
    counts.setdefault(item,0)
    counts[item]+=1

ent = 0
for i in counts:
    p = float(counts[i])/total
    ent-=p*log2(p)
return -ent*log2(1/ent)

def upload(request):
filename = request.FILES['search_field']

#return render(request,'temp.html',{'A': filename})
  #conn=mysql.connector.connect(user="root",password="28091994",host="localhost",database="images")
#mycursor=conn.cursor()


rms=rootmeansquare(filename)
var=varaince(filename)
#sd=standarddeviation(filename)
#edge=edgedetection(filename)
#histv=histogramvalue(filename)
#ev=entropy(filename)
#fvsum=rms+sd+edge+histv+ev
fvavg=float(rms/7)
#mycursor.execute("INSERT INTO fva(img,fvavg) VALUES (%s, %s)",   (filename, fvavg))
#conn.commit()
#a=fva(img=filename,fvavg=fvavg)
#a.save()
return render(request,'index.html',{})