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# -*- coding:utf-8 -*-
#import numpy
from PIL import Image
class Dither:
def __init__(self,image_path):
self.imgdata = Image.open(image_path).resize((128,128)).convert("L")
#self.imgarray = numpy.asarray(self.imgdata)
def error_diffusion(self):
data = self.imgdata.convert(mode="1",dither=1)
#maxcol, maxrow = self.imgdata.size
#outarray = numpy.copy(self.imgarray)
#self.imgarray.flags.writeable = True
#for i in xrange(maxrow):
# for j in xrange(maxcol):
# if self.imgarray[i,j] > 0 :
# outarray[i,j] = 1
# else:
# outarray[i,j] = 0
#print( str(self.imgarray[i,j]) +"," + str(outarray[i,j]))
#error = 0
#if self.imgarray[i,j] > 127:
# eroor = self.imgarray[i,j] -255
# outarray[i,j] = 1
#else:
# eroor = self.imgarray[i,j]
# outarray[i,j] = 0
#if(i+1 != maxrow):
# self.imgarray[i+1][j] += 5/16 * error
# if(j+1 != maxcol):
# self.imgarray[i+1][j+1] += 3/16 * error
#if(j+1 != maxcol):
# self.imgarray[i][j+1] += 5/16 * error
# if(i != 0):
# self.imgarray[i-1][j+1] += 3/16 * error
#data = self.decode_img(numpy.uint8(outarray))
return data
def decode_img(self,img_array):
return Image.fromarray(img_array,mode="1")
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