import numpy as np import math from PIL import Image from scipy import interpolate from scipy import stats from PIL import ImageOps import cv2 import list import threading # import pyopencl as cl

def echantillonageRadial(image, beamNumber, pxPerBeam, angle, height, dmin, dmax):

longeur, largeur = image.size image = list(image.getdata()) image = [image[i * largeur:(i + 1) * largeur] for i in range(longeur)] # Base sortie imageSortie = np.zeros((longeur, largeur)) i = (3 * math.pi - angle) / 2 while i < (3 * math.pi + angle) / 2:

System Message: ERROR/3 (C:\Users\polch_000\PycharmProjects\digiSimul\AjoutBruit.py, line 20)

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j = dmin while j < dmax:

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x = j * math.cos(i) + largeur / 2 y = -j * math.sin(i) + height x = int(x) y = int(y) imageSortie[x][y] = image[x][y]

j += (((3 * math.pi + angle) / 2) - ((3 * math.pi - angle) / 2)) / (pxPerBeam - 1)

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i += (dmax - dmin) / (beamNumber - 1)

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return imageSortie

def echantillonageRect(npimage, longeur, largeur, nbPointAbscisse, nbpointOrdonnee):

# Image base sortie : imageSortie = np.ones((longeur, largeur))-2 y = 0 while y < largeur:

System Message: ERROR/3 (C:\Users\polch_000\PycharmProjects\digiSimul\AjoutBruit.py, line 38)

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x=0 while x < longeur:

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imageSortie[int(x)][int(y)] = npimage[int(x)][int(y)] x += largeur

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y += longeur/ nbpointOrdonnee

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return imageSortie

def echantillonageRect2(npimage,nbPoint):

"""

param npimage:	Image à echantilloner en format numpy
param nbPoint:	Ratio des points que l'on veut garder : 1 sur nbpoint
return:	Image echantillonée sous forme de tableau numpy

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""" longeur,largeur = npimage.shape y = 0 while y < int(largeur/nbPoint):

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again = 1 while again < nbPoint:

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npimage = np.delete(npimage,(y),axis=1) again += 1

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y += 1

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x = 0 while x < int(longeur/nbPoint):

System Message: ERROR/3 (C:\Users\polch_000\PycharmProjects\digiSimul\AjoutBruit.py, line 63)

Unexpected indentation.

again = 1 while again < nbPoint:

System Message: ERROR/3 (C:\Users\polch_000\PycharmProjects\digiSimul\AjoutBruit.py, line 65)

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npimage = np.delete(npimage,(x),axis=0) again += 1

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x += 1

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return npimage

def AjoutSpeckel( img, borneInf, borneSup, ecartTypeGauss, u):

longeur,largeur = img.shape #matrices de vecteurs gaussiens beta = 8 alpha = 1.98 # matrixGauss = stats.gennorm.rvs(beta,scale=alpha,loc=0,size=longeur*longeur*u).reshape(longeur, largeur, u) # matrixGauss2 = stats.gennorm.rvs(beta,scale=alpha,loc=0,size=longeur*longeur*u).reshape(longeur, largeur, u) # matrixGauss = (stats.levy_stable_gen.rvs(alpha, 0,size = longeur*largeur*u,scale=gama).reshape(longeur, largeur, u)) # matrixGauss2 = (stats.levy_stable_gen.rvs(alpha,0,size = longeur*largeur*u,scale=gama).reshape(longeur, largeur, u)) matrixGauss = np.random.randn(longeur * largeur, u).reshape(longeur, largeur, u) matrixGauss2 = np.random.randn(longeur * largeur, u).reshape(longeur, largeur, u) imgRetour = np.sqrt(img + 0j) i = 0 while i < u-1:

System Message: ERROR/3 (C:\Users\polch_000\PycharmProjects\digiSimul\AjoutBruit.py, line 85)

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imgRetour += (matrixGauss[:,:,i]) + (matrixGauss2[:,:,i]*1j) i += 1

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img = np.square(imgRetour.real) + np.square(imgRetour.imag) return img

def interpolation(img):

""" Interpolation bicubique :param img: Image à interpoler sous forme de tableau numpy :return: Fonction d'interpoaltion de l'image """ img = np.zeros(img.shape) + img l,L = img.shape x = np.arange(0,l,1) y = np.arange(0, L, 1) X,Y = np.meshgrid(x,y) fonctionInter = interpolate.interp2d(x,y,img, kind='cubic') return fonctionInter

def construireImageInterpelee(function,l,L,nbPoint):

""" Reconstruit une image grâce à une R² -> R :param function: Une fonction de R² dans R :param l: Longeur de l'image voulu :param L: Largeur de l'image voulu :param nbPoint: Nombre de point à interpoler :return: Un tableau numpy bidimentionnel représentant une image """ x = np.arange(0, l/nbPoint,1/nbPoint) y = np.arange(0, L/nbPoint,1/nbPoint) img = function(x,y) return img

def AjoutBruit(image):

""" Fonction principale appelant les méthodes permettant d'ajouter un bruit de peckel à image de type optique

param image:	Une image provenant de la bibliothèque "PIL Image"
return:	Un tableau bidimentionel numpy représentant une image

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""" # conversion de l'image en array numpy nbPoint = 2 l,L = image.shape img = echantillonageRect2(image,nbPoint) img4 = AjoutSpeckel(img, 1,1 , 0.2,3) img5 = interpolation(img4) img5 = construireImageInterpelee(img5,l,L,nbPoint) return img5

def AjoutBruitMultiThreah():

""" Produit plusieurs threads permettant d'utiliser tous les coeurs pour l'ajout du bruit de speckel :return: Void """ img = cv2.imread("images/vador.bmp") img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) t1 = threading.Thread(target=multipleImage,args=(img,1)) t2 = threading.Thread(target=multipleImage,args=(img,2)) t3 = threading.Thread(target=multipleImage,args=(img,3)) t4 = threading.Thread(target=multipleImage,args=(img,4)) t5 = threading.Thread(target=multipleImage,args=(img,5)) t6 = threading.Thread(target=multipleImage,args=(img,6)) t7 = threading.Thread(target=multipleImage,args=(img,7)) t1.start() t2.start() t3.start() t4.start() t5.start() t6.start() t7.start() return 0;

def multipleImage(img,p):

it = 0 while it < 10:

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Unexpected indentation.

print(it) img2 = AjoutBruit(img) img3 = Image.fromarray(img2).

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save("imgT1It%sP%s"%(it,p),"gif")

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it += 1

def trouveAlphaGama():

img = cv2.imread("images/01_d_3.bmp") img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) l,L = img.shape y = -1 somme = 0 sommeC = 0 cpt = 0 a = [0] while y < L-1:

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y +=1 x = -1 while x < l-1:

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print(x,y) x += 1 if ( img

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[x][y] != 0):

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a.append(img[x][y])

print(a) esp = np.mean(a,dtype=np.float64) var = np.var(a,dtype=np.float64) alpha = np.sqrt(np.square(math.pi)/(6*var)) gama = math.exp( alpha * (esp - math.log(2,10) - 0.577215664901532860606512090082402431042159335939923598805*((1/alpha)-1) )) print(esp,var,alpha,gama)

# MAIN img = cv2.imread("images/fg1.bmp") img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) AjoutBruit(img)

# # GPU # # creer un contexte # myContext = cl.create_some_context() # # creer une file de commandes # myQueue = cl.CommandQueue(myContext) # # allouer et initialiser la memoire du device # inputData = np.random.rand(50000).astype(np.float32) # outputData = np.empty_like(inputData) # myFlags = cl.mem_flags # inputBuffer = cl.Buffer(myContext, # myFlags.READ_ONLY | myFlags.COPY_HOST_PTR, hostbuf=inputData) # outputBuffer = cl.Buffer(myContext, myFlags.WRITE_ONLY, inputData.nbytes) # # charger et compiler le kernel # myProgram = cl.Program(myContext, # """__kernel void add42(__global const float *data, __global float *result){int gid = get_global_id(0);result[gid] = data[gid] + 42.f;}""").build() # # ajouter le kernel dans la file de commandes # # recuperer les donnees dans la memoire du device # myProgram.add42(myQueue, inputData.shape,None, inputBuffer, outputBuffer) # cl.enqueue_copy(myQueue, outputData, outputBuffer) # # verifier le resultat du calcul # if abs(np.linalg.norm(outputData - (inputData + 42))) < 1e-6 : # print("passed") # else: # print("failed") #