Einfügen eines Dalt-Buttons in die GUI
Zum Aufrufen des Algorithmus in der GUI muss ein Button Objekt der tkinter Klasse erstellt werden. Dieses wird erst nach einem erfolgreich ausgewählten Bild aktiv! Als nächstes steht die Implementation der daltonize-Funktion an, die durch command='daltonize' ausgeführt wird.
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Max Sponsel
parent
8498500c68
commit
137ca981f2
@ -23,18 +23,20 @@ sim_deut = tk.IntVar(root)
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sim_tri = tk.IntVar(root)
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simulationsGradient = tk.Scale(SB.frame, from_=0, to_=100, variable=simGrad, orient='horizontal')
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simulationsGradient.grid(column= 0, row = 1, columnspan=10)
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simulationsGradient.grid(column=0, row=1, columnspan=10)
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def browse():
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# Auswahl des FilePaths
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try:
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path = tk.filedialog.askopenfilename(filetypes=[("Image File", '.jpg'),("Image File", '.png')])
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path = tk.filedialog.askopenfilename(filetypes=[("Image File", '.jpg'), ("Image File", '.png')])
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im = Image.open(path)
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except:
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tk.messagebox.showerror(title='Datenfehler', message='Kein Bild gefunden/ausgewählt')
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global simulateButton
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if len(path) > 0:
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simulateButton.config(state='active')
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daltonButton.config(state='active')
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# Anzeigen des Bildes
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tkimage = ImageTk.PhotoImage(im)
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@ -52,12 +54,12 @@ def browse():
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def simulate():
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global img, rows, cols, kanaele, sim_pro, sim_deut, sim_tri
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if sim_deut.get():
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d = Dyschromasie(img, rows, cols, kanaele, simGrad.get()/100, 'd')
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d = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 'd')
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display_array_deut = np.copy(d.Simulate()).astype('uint8')
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T = tk.Text(SB.frame, height=1, width=15)
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T.grid(columnspan=5)
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print_string = "Deutranop(" + str(round(d.sim_faktor*100)) + "%)"
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print_string = "Deutranop(" + str(round(d.sim_faktor * 100)) + "%)"
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T.insert('current', print_string)
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conv_SimulationPic_deut = ImageTk.PhotoImage(image=PIL.Image.fromarray(display_array_deut))
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@ -65,7 +67,7 @@ def simulate():
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sim_pic_deut.Image = conv_SimulationPic_deut
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sim_pic_deut.grid(columnspan=5)
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elif sim_tri.get():
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t = Dyschromasie(img, rows, cols, kanaele, simGrad.get()/100, 't')
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t = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 't')
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display_array_tri = np.copy(t.Simulate()).astype('uint8')
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T = tk.Text(SB.frame, height=1, width=15)
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@ -78,7 +80,7 @@ def simulate():
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sim_pic_tri.Image = conv_SimulationPic_tri
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sim_pic_tri.grid(columnspan=5)
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elif sim_pro.get():
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p = Dyschromasie(img, rows, cols, kanaele, simGrad.get()/100, 'p')
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p = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 'p')
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display_array_pro = np.copy(p.Simulate()).astype('uint8')
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T = tk.Text(SB.frame, height=1, width=15)
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@ -92,13 +94,22 @@ def simulate():
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sim_pic_pro.grid(columnspan=5)
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btn = tk.Button(SB.frame, text="Browse", width=25, command=browse, bg='light blue')
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btn.grid(column=0, row=0, columnspan=2)
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def daltonize():
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#ToDo
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print("working")
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browseButton = tk.Button(SB.frame, text="Browse", width=25, command=browse, bg='light blue')
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browseButton.grid(column=0, row=0, columnspan=1)
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simulateButton = tk.Button(SB.frame, text="Simulate", width=25, command=simulate, bg='light blue')
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simulateButton.grid(column=1, row=0, columnspan=2)
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simulateButton.grid(column=1, row=0, columnspan=1)
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simulateButton.config(state='disabled')
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daltonButton = tk.Button(SB.frame, text="Daltonize", width=25, command=daltonize, bg='light blue')
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daltonButton.grid(column=2, row=0, columnspan=1)
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daltonButton.config(state='disabled')
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checkButton_p = tk.Checkbutton(SB.frame, text="Protanop", variable=sim_pro, onvalue=1, offvalue=0, height=5, width=20)
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checkButton_d = tk.Checkbutton(SB.frame, text="Deutanop", variable=sim_deut, onvalue=1, offvalue=0, height=5, width=20)
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checkButton_t = tk.Checkbutton(SB.frame, text="Tritanop", variable=sim_tri, onvalue=1, offvalue=0, height=5, width=20)
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@ -21,7 +21,7 @@ def removeGammaCorrection(v):
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def applyGammaCorrection(v_reverse):
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if abs(v_reverse) <= 0.0031308:
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return round(255 * (12.92 * abs(v_reverse)))
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elif abs(v_reverse) > 0.0031308:
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else:
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if (round(255 * (1.055 * abs(v_reverse) ** 0.41666 - 0.055))) > 255:
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return 255 - (round(255 * (1.055 * abs(v_reverse) ** 0.41666 - 0.055)) - 255)
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else:
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@ -30,7 +30,7 @@ def applyGammaCorrection(v_reverse):
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class Dyschromasie:
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cb_image = np.array([]).astype('float64')
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sim_image = np.array([]).astype('uint8')
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sim_image = np.array([]).astype('int64')
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def __init__(self, img_mat=np.array([]), rows=0, cols=0, kanaele=0, sim_faktor=0, sim_kind='d'):
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self.rows = rows
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@ -49,7 +49,6 @@ class Dyschromasie:
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[0.02980165, -0.19318073, 1.16364789]])
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def Simulate(self):
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removeGammaCorrectionLUT = createGammaLookup()
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if self.sim_kind == 'p':
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@ -78,14 +77,14 @@ class Dyschromasie:
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self.cb_image[i, j] = rechen_Mat.dot(self.cb_image[i, j])
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self.sim_image = np.copy(self.cb_image)
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self.sim_image = self.sim_image.astype('uint8')
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self.sim_image = self.sim_image.astype('int64')
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# Rücktransformation der Gammawerte
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for i in range(self.rows):
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for j in range(self.cols):
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for x in range(3):
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self.sim_image[i, j, x] = applyGammaCorrection(self.cb_image[i, j, x])
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return self.sim_image
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return self.sim_image.astype('uint8')
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def daltonize(self):
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@ -109,17 +108,17 @@ class Dyschromasie:
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for i in range(self.rows):
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for j in range(self.cols):
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for x in range(3):
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dtpn[i, j, x] = abs(int(ERR[i, j, x]) + int(image[i, j, x]))
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for x in range(3):
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dtpn[i, j, x] = abs(int(ERR[i, j, x]) + int(image[i, j, x]))
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for i in range(rows):
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for j in range(cols):
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dtpn[i, j, 0] = max(0, dtpn[i, j, 0])
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dtpn[i, j, 0] = min(255, dtpn[i, j, 0])
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dtpn[i, j, 1] = max(0, dtpn[i, j, 1])
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dtpn[i, j, 1] = min(255, dtpn[i, j, 1])
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dtpn[i, j, 2] = max(0, dtpn[i, j, 2])
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dtpn[i, j, 2] = min(255, dtpn[i, j, 2])
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for j in range(cols):
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dtpn[i, j, 0] = max(0, dtpn[i, j, 0])
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dtpn[i, j, 0] = min(255, dtpn[i, j, 0])
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dtpn[i, j, 1] = max(0, dtpn[i, j, 1])
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dtpn[i, j, 1] = min(255, dtpn[i, j, 1])
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dtpn[i, j, 2] = max(0, dtpn[i, j, 2])
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dtpn[i, j, 2] = min(255, dtpn[i, j, 2])
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result = dtpn.astype('uint8')
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@ -127,12 +126,15 @@ class Dyschromasie:
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return dalt.Simulate()
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script_dir = sys.path[0]
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path = script_dir[:-4] + r'Beispielbilder\rot-gruen-schwaeche-test-bild.jpg'
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image = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2RGB)
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def main():
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script_dir = sys.path[0]
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path = script_dir[:-4] + r'Beispielbilder\rot-gruen-schwaeche-test-bild.jpg'
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image = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2RGB)
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rows, cols, kanaele = image.shape
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rows, cols, kanaele = image.shape
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dalt = Dyschromasie(image, rows, cols, kanaele, 1, 'p')
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cv2.imshow('Dalt_Img', cv2.cvtColor(dalt.daltonize(), cv2.COLOR_RGB2BGR))
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cv2.waitKey(0)
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dalt = Dyschromasie(image, rows, cols, kanaele, 1, 'p')
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cv2.imshow('Dalt_Img', cv2.cvtColor(dalt.daltonize(), cv2.COLOR_RGB2BGR))
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cv2.waitKey(0)
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# main()
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