Hi Xavi, Sorry for the long delay in responding. I'm excited about your GUI! If you have it on GitHub somewhere, please point us to it, as it would be a great template for others to build from! Regarding your black image problem, my guess is that you are having some issues with the data types in skimage. Your input image is a uint8 image (?), with range [0, 255], but filters.gaussian runs it through our conversion to a float image, which results in the range [0.0, 1.0]. Some displays will still display this as though the full range is in [0, 255], so the image will appear black. You probably need to back-convert to int using skimage.img_as_ubyte. See: http://scikit-image.org/docs/dev/user_guide/data_types.html I hope that helps. Again, please point us to your repo if you are happy to share! Juan. On 8 October 2016 at 8:12:13 am, xavi barrull (xavi_barrull@hotmail.com) wrote: Hi, I have a question about scikit image. I make a GUI in python to processing image, but I will change the gaussian Filter in opencv to scikit image, I use this function: def gaussFilter(self): targetTemp = sk.io.imread(self.original_path)# llegir imatge targetTemp a la ruta original targetTemp = sk.filters.gaussian(targetTemp, sigma=0, mode='reflect', cval=0, multichannel=False) #targetTemp = cv2.GaussianBlur(targetTemp,(sigmaX, sigmaY), 0) cv2.imwrite(self.target_path,targetTemp) self.updateTargetImage() But, when I press the button of gaussian filter the image to update becomes black, what is the problem? I need a solution for this! My code show bellow: import Tkinter as tk import numpy as np import tkFileDialog import tkMessageBox import shutil import os from PIL import Image, ImageTk, ImageFilter import cv2 import colormaps import skimage as sk import matplotlib.pyplot as plt from matplotlib.colors import ListedColormap from matplotlib.figure import Figure from skimage import filters from skimage import io from skimage.morphology import disk from skimage.filters.rank import median from skimage.filters import gaussian from skimage.morphology import watershed from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg class App(tk.Frame): size = 500, 700 # get past scale value past=1 # inicialitzar app def __init__(self, master): tk.Frame.__init__(self, master) self.grid(row=0) self.columnconfigure(0, weight=1) self.rowconfigure(0, weight=1) master.geometry("1024x768") self.generateMenu(master) # Generacio Menu def generateMenu(self, master): # crear barra menu, dins de la llibreria TKinter (tk.) self.menuBar=tk.Menu(self) # creacio arxiu dins de la barra de menu self.fileMenu=tk.Menu(self.menuBar, tearoff=0) # crear commandes obrir, guardar i tancar, l'estat de guardar esta desactivat mentre no s'obri una imatge self.fileMenu.add_command(label="Open", command=self.open) self.fileMenu.add_command(label="Save", command=self.save, state="disabled") self.fileMenu.add_command(label="Close", command=self.exit) # Afegim tot aixo la barra de menu en cascada self.menuBar.add_cascade(label="File", menu=self.fileMenu) # Crear menu de process self.processMenu=tk.Menu(self.menuBar, tearoff=0) # crear submenu de processs/filter self.processFilterSubMenu = tk.Menu(self.processMenu, tearoff=0) self.processFilterSubMenu.add_command(label="Gaussian Filter", command=self.gaussFilter, state="disabled") self.processFilterSubMenu.add_command(label="Median Filter", command=self.medianFilter, state="disabled") self.processMenu.add_cascade(label="Process/Filter", menu=self.processFilterSubMenu, underline=0) # crear submenu segmentacio self.segmentationSubMenu = tk.Menu(self.processMenu, tearoff=0) self.segmentationSubMenu.add_command(label="Watershed", command=self.watershed, state="disabled") self.segmentationSubMenu.add_command(label="Random walker", command=self.randomwalker, state="disabled") self.processMenu.add_cascade(label="Segmentation", menu=self.segmentationSubMenu, underline=0) # crear submenu edgeDetection self.edgeDetectionSubMenu = tk.Menu(self.processMenu, tearoff=0) self.edgeDetectionSubMenu.add_command(label="Sobel", command=self.sobel, state="disabled") self.edgeDetectionSubMenu.add_command(label="Laplacian", command=self.laplacian, state="disabled") self.edgeDetectionSubMenu.add_command(label="Canny", command=self.canny, state="disabled") self.processMenu.add_cascade(label="Edge Detection", menu=self.edgeDetectionSubMenu, underline=0) # crear submenu change colormap self.colorMapSubMenu = tk.Menu(self.processMenu, tearoff=0) self.colorMapSubMenu.add_command(label="None", command=self.none, state="disabled") self.colorMapSubMenu.add_command(label="Plasma", command=self.plasma, state="disabled") self.colorMapSubMenu.add_command(label="Inferno", command=self.inferno, state="disabled") self.colorMapSubMenu.add_command(label="Viridis", command=self.viridis, state="disabled") self.processMenu.add_cascade(label="Change Colormap", menu=self.colorMapSubMenu, underline=0) self.menuBar.add_cascade(label="Process", menu=self.processMenu) master.config(menu=self.menuBar) # No colorMap def none(self): targetTemp = cv2.imread(self.original_path) cv2.imwrite(self.target_path,targetTemp)# guarda imatge targetTemp i a la ruta de desti self.updateTargetImage() # Plasma colorMap def plasma(self): plt.clf()#esborra imatge targetTemp targetTemp = cv2.imread(self.original_path) # llegir ruta original (carpeta on es troba arxiu py) targetTemp = np.fliplr(targetTemp[:,:,0]) # gir esquerra a dreta imatge original, segons 3r valor matriu, varia tonalitat plasma = ListedColormap(colormaps._plasma_data, name='plasma') plt.axis('off')#desactiva eixos a la imatge plt.register_cmap(name='plasma', cmap=plasma) # registrar colormap nou i aplicar-lo imgplot = plt.imshow(targetTemp)#mostrar imatge allotjada a targetTemp imgplot.set_cmap(plasma)#aplicar colormap imgplot.figure.savefig(self.target_path)#guardar imatge com a figura a la ruta de desti self.updateTargetImage() #actualitzar la imatge (amb aplicacio del colormap) def viridis(self): plt.clf() #esborra imatge targetTemp targetTemp = cv2.imread(self.original_path) targetTemp = np.fliplr(targetTemp[:,:,0]) viridis = ListedColormap(colormaps._viridis_data, name='viridis') plt.axis('off') plt.register_cmap(name='viridis', cmap=viridis) imgplot = plt.imshow(targetTemp) imgplot.set_cmap(viridis) imgplot.figure.savefig(self.target_path) # update target screen self.updateTargetImage() def inferno(self): plt.clf() targetTemp = cv2.imread(self.original_path) targetTemp = np.fliplr(targetTemp[:,:,0]) inferno = ListedColormap(colormaps._inferno_data, name='inferno') plt.axis('off') plt.register_cmap(name='inferno', cmap=inferno) imgplot = plt.imshow(targetTemp) imgplot.set_cmap(inferno) imgplot.figure.savefig(self.target_path) self.updateTargetImage() # funcio per obrir arxius def open(self): # obrir arxiu des del quadre de dialeg self.original_path = tkFileDialog.askopenfilename(filetypes=[("Image Files","*.jpg;*.jpeg;*.png;*.gif")]) if self.original_path!="": # si es selecciona un arxiu, s'activen totes les comandes del menu self.fileMenu.entryconfig("Save", state="normal") self.processFilterSubMenu.entryconfig("Gaussian Filter", state="normal") self.processFilterSubMenu.entryconfig("Median Filter", state="normal") self.segmentationSubMenu.entryconfig("Watershed", state="normal") self.segmentationSubMenu.entryconfig("Random walker", state="normal") self.edgeDetectionSubMenu.entryconfig("Sobel", state="normal") self.edgeDetectionSubMenu.entryconfig("Laplacian", state="normal") self.edgeDetectionSubMenu.entryconfig("Canny", state="normal") self.colorMapSubMenu.entryconfig("None", state="normal") self.colorMapSubMenu.entryconfig("Plasma", state="normal") self.colorMapSubMenu.entryconfig("Inferno", state="normal") self.colorMapSubMenu.entryconfig("Viridis", state="normal") saveButton = tk.Button(self, text="Save", command=self.save) saveButton.grid(row=7, column=10) self.actual_name = self.original_path[self.original_path.rfind("/"):self.original_path.rfind(".")] #creacio arxiu temporal de la imatge que hem obert self.target_path = self.original_path[0:self.original_path.rfind(".")]+"imatge."+self.original_path[self.original_path.rfind(".")+1:] shutil.copy2(self.original_path, self.target_path) #copia l'arxiu de la ruta original #os.popen('attrib +h ' + self.target_path) self.originalImg = Image.open(self.original_path) #obrir imatge original self.originalImg.thumbnail(App.size, Image.ANTIALIAS) #thumbnail-> aplica mida imatge escalada a la finestra App.size originalImgCanvas = tk.Canvas(self, width= 500, height=380) # aplica la mida especificada a la imatge original originalImgCanvas.grid(row=3, column=2, columnspan=6) # la posiciona dins del grid a la fila 3 i la columna 2, abasta 6 columnes tkOriginalImg = ImageTk.PhotoImage(self.originalImg) # mostra la imatge original self.originalImg.image = tkOriginalImg # associa la imatge original a la imatge dins la llibreria tkinter originalImgCanvas.create_image(100,100,image=tkOriginalImg, anchor=tk.NW, tags="IMG") # crea la imatge anterior amb amplada nord-oest dins del widget de Canvas que disposa d'estructures grafiques self.targetImg = Image.open(self.target_path)# obrir imatge a procesar self.targetImg.thumbnail(App.size, Image.ANTIALIAS) #thumbnail-> aplica mida imatge escalada a la finestra App.size self.targetImgCanvas = tk.Canvas(self, width= 500, height=380) self.targetImgCanvas.grid(row=3, column=8, columnspan=6) self.tkTargetImg = ImageTk.PhotoImage(self.targetImg) self.targetImg.image = self.tkTargetImg self.targetImgCanvas.create_image(100,100,image=self.tkTargetImg, anchor=tk.NW) # source histogram #originalCvImg = cv2.imread(self.original_path) #plt.figure(figsize=(2,2)) #color = ('b','g','r') #for channel,col in enumerate(color): # histr = cv2.calcHist([originalCvImg],[channel],None,[256],[0,256]) # plt.plot(histr,color = col) # plt.xlim([0,256]) # if( col == 'b'): # originalB=plt.imshow(histr).figure # elif( col == 'g'): # originalG=plt.imshow(histr).figure # else: # originalR=plt.imshow(histr).figure #self.NewCanvas = tk.Canvas(self, width= 30, height=50) #self.canvas = FigureCanvasTkAgg(originalR, master=self.NewCanvas) #self.NewCanvas.grid(row=4, column=0) #self.canvas.show() #self.canvas.get_tk_widget().grid(row=0, column=0) # target histogram #targetCvImg = cv2.imread(self.target_path) #plt.figure(figsize=(2,2)) #color = ('b','g','r') #for channel,col in enumerate(color): # histr = cv2.calcHist([targetCvImg],[channel],None,[256],[0,256]) # plt.plot(histr,color = col) # plt.xlim([0,256]) # if( col == 'b'): # targetB=plt.imshow(histr).figure # elif( col == 'g'): # targetG=plt.imshow(histr).figure # else: # targetR=plt.imshow(histr).figure #self.NewTargetCanvas = tk.Canvas(self, width= 30, height=50) #self.canvasTarget = FigureCanvasTkAgg(targetR, master=self.NewTargetCanvas) #self.NewTargetCanvas.grid(row=4, column=1) #self.canvasTarget.show() #self.canvasTarget.get_tk_widget().grid(row=0, column=0) # to have only odd value in scale def fix(self, xy, n): #no entenc que fa aquesta funcio! global past n = int(n) if not n % 2: if xy=="sx": scale = self.gaussianSigmaXScale elif xy=="sy": scale = self.gaussianSigmaYScale elif xy=="median": scale = self.medianSizeScale else: scale = self.kernelSizeScale scale.set(n+1 if n > self.past else n-1) self.past = scale.get() # funcio per guardar imatges procesades def save(self): if tkMessageBox.askokcancel("Save", "Do you want to save?"): os.remove(self.original_path)# esborra arxiu original de la ruta de desti os.popen('attrib -h -s ' + self.target_path)# obre arxiu target de # la ruta de desti, correspon imatge a processar os.rename(self.target_path, self.original_path) #renombra # la imatge original i la imatge a processar shutil.copy2(self.original_path, self.target_path) #copia l'arxiu # de la ruta original i tambe la imatge a processar (target) os.popen('attrib +h ' + self.target_path) # sortir del GUI def exit(self): if tkMessageBox.askokcancel("Quit", "Do you want to quit?"): try: # esborrar arxiu temporal os.remove(self.target_path) finally: self.master.destroy() def updateTargetImage(self): # funcio per actualitzar les diferents accio a la imatge a procesar self.targetImg = Image.open(self.target_path) # obre la imatge a procesar, en la ruta on es troba self.targetImg.thumbnail(App.size, Image.ANTIALIAS) #thumbnail-> aplica mida imatge escalada a la finestra App.size self.tkTargetImg = ImageTk.PhotoImage(self.targetImg)# mostra la imatge a procesar self.targetImg.image = self.tkTargetImg # associa la imatge a procesar a la imatge dins la llibreria Tkinter (que allotja tot el referent al GUI) self.targetImgCanvas.create_image(5,5,image=self.tkTargetImg, anchor=tk.NW, tags="IMG") # crea la #imatge a procesar quan se li aplica algun canvi (colormap, filtres, etc) targetCvImg = cv2.imread(self.target_path) # llegeix la imatge de la ruta de desti plt.figure(figsize=(4,4)) # crea una figura per allotjar histograma color = ('b','g','r') for i,col in enumerate(color): histr = cv2.calcHist([targetCvImg],[i],None,[256],[0,256]) plt.plot(histr,color = col) plt.xlim([0,256]) targetR=plt.imshow(histr).figure self.NewTargetCanvas = tk.Canvas(self, width= 30, height=50) #crea un nou # Canvas de la mida indicada self.canvasTarget = FigureCanvasTkAgg(targetR, master=self.NewTargetCanvas) #crea una figura dins del Canvas on s'allotja el histograma self.NewTargetCanvas.grid(row=4, column=1)# defineix posicio del grid dins el # Canvas self.canvasTarget.show() # mostra el canvas self.canvasTarget.get_tk_widget().grid(row=0, column=0) def gaussFilter(self): targetTemp = sk.io.imread(self.original_path)# llegir imatge targetTemp a la ruta original targetTemp = sk.filters.gaussian(targetTemp, sigma=0, mode='reflect', cval=0, multichannel=False) #targetTemp = cv2.GaussianBlur(targetTemp,(sigmaX, sigmaY), 0)#aplicar filtre cv2.imwrite(self.target_path,targetTemp) # actualitzar imatge Target self.updateTargetImage() My code is so long (There are another functions or filters (Sobel, Canny, etc...) I paste the finally: def on_closing(app, root): if tkMessageBox.askokcancel("Quit", "Do you want to quit?"): try: os.remove(app.target_path) except: print("error") finally: root.destroy() # inicialitzar llibreria Tkinter per creacio widget root=tk.Tk() app = App(root) # renderitzar GUI, to accept events root.protocol("WM_DELETE_WINDOW", lambda: on_closing(app, root)) app.mainloop() I attached image about my problema I need help, it's so urgent! Thanks in advance. Xavi. _______________________________________________ scikit-image mailing list scikit-image@python.org https://mail.python.org/mailman/listinfo/scikit-image