Browse Source

Dalt Algorithmus und Auslagern des Displays

Der Dalt Algorithmus wird nun von dem Dalt-Button ausgeführt. Gleichzeitig wurde die Funktion showImage geschrieben, um Code zu verschlanken und lediglich die Switchfunktionen simulate und daltonize für die Auswahl der Simulationsart zu nutzen.
PS: Mehrere Bilder zum Testen eingefügt
master
Max Sponsel 3 years ago
parent
commit
a206147edf

BIN
Beispielbilder/Ishihara-Plate-Tritanop12.jpg View File


BIN
Beispielbilder/Ishihara-Plate-Tritanop42.jpg View File


+ 31
- 37
Code/Dyschromasie-Applikation.py View File

@@ -51,52 +51,46 @@ def browse():
rows, cols, kanaele = img.shape
def showImage(img, rows, cols, kanaele, sim_faktor, sim_kind, sim_art):
color_blindness = Dyschromasie(img, rows, cols, kanaele, sim_faktor, sim_kind)
if sim_art == 'Sim':
color_blindness_mat = np.copy(color_blindness.Simulate()).astype('uint8')
else:
color_blindness_mat = np.copy(color_blindness.daltonize()).astype('uint8')
T = tk.Text(SB.frame, height=1, width=15)
T.grid(columnspan=5)
print_string = sim_kind + ' ' + str(round(color_blindness.sim_faktor * 100)) + "%)"
T.insert('current', print_string)
conv_SimulationPic = ImageTk.PhotoImage(image=PIL.Image.fromarray(color_blindness_mat))
sim_pic = tk.Label(SB.frame, image=conv_SimulationPic)
sim_pic.Image = conv_SimulationPic
sim_pic.grid(columnspan=5)
def simulate():
global img, rows, cols, kanaele, sim_pro, sim_deut, sim_tri
if sim_deut.get():
d = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 'd')
display_array_deut = np.copy(d.Simulate()).astype('uint8')
T = tk.Text(SB.frame, height=1, width=15)
T.grid(columnspan=5)
print_string = "Deutranop(" + str(round(d.sim_faktor * 100)) + "%)"
T.insert('current', print_string)
conv_SimulationPic_deut = ImageTk.PhotoImage(image=PIL.Image.fromarray(display_array_deut))
sim_pic_deut = tk.Label(SB.frame, image=conv_SimulationPic_deut)
sim_pic_deut.Image = conv_SimulationPic_deut
sim_pic_deut.grid(columnspan=5)
showImage(img, rows, cols, kanaele, simGrad.get()/100, 'Deuteranop', 'Sim')
elif sim_tri.get():
t = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 't')
display_array_tri = np.copy(t.Simulate()).astype('uint8')
T = tk.Text(SB.frame, height=1, width=15)
T.grid(columnspan=5)
print_string = "Tritanop(" + str(round(t.sim_faktor * 100)) + "%)"
T.insert('current', print_string)
conv_SimulationPic_tri = ImageTk.PhotoImage(image=PIL.Image.fromarray(display_array_tri))
sim_pic_tri = tk.Label(SB.frame, image=conv_SimulationPic_tri)
sim_pic_tri.Image = conv_SimulationPic_tri
sim_pic_tri.grid(columnspan=5)
showImage(img, rows, cols, kanaele, simGrad.get() / 100, 'Tritanop', 'Sim')
elif sim_pro.get():
p = Dyschromasie(img, rows, cols, kanaele, simGrad.get() / 100, 'p')
display_array_pro = np.copy(p.Simulate()).astype('uint8')
showImage(img, rows, cols, kanaele, simGrad.get() / 100, 'Protanop', 'Sim')
T = tk.Text(SB.frame, height=1, width=15)
T.grid(columnspan=5)
print_string = "Protanop(" + str(round(p.sim_faktor * 100)) + "%)"
T.insert('current', print_string)
conv_SimulationPic_pro = ImageTk.PhotoImage(image=PIL.Image.fromarray(display_array_pro))
sim_pic_pro = tk.Label(SB.frame, image=conv_SimulationPic_pro)
sim_pic_pro.Image = conv_SimulationPic_pro
sim_pic_pro.grid(columnspan=5)
def daltonize():
global img, rows, cols, kanaele, sim_pro, sim_deut, sim_tri
if sim_deut.get():
showImage(img, rows, cols, kanaele, simGrad.get()/100, 'Deuteranop', 'Dalt')
elif sim_tri.get():
showImage(img, rows, cols, kanaele, simGrad.get() / 100, 'Tritanop', 'Dalt')
def daltonize():
#ToDo
print("working")
elif sim_pro.get():
showImage(img, rows, cols, kanaele, simGrad.get() / 100, 'Protanop', 'Dalt')
browseButton = tk.Button(SB.frame, text="Browse", width=25, command=browse, bg='light blue')

+ 9
- 22
Code/Farbaenderung.py View File

@@ -32,7 +32,7 @@ class Dyschromasie:
cb_image = np.array([]).astype('float64')
sim_image = np.array([]).astype('int64')
def __init__(self, img_mat=np.array([]), rows=0, cols=0, kanaele=0, sim_faktor=0, sim_kind='d'):
def __init__(self, img_mat=np.array([]), rows=0, cols=0, kanaele=0, sim_faktor=0, sim_kind='Deuteranop'):
self.rows = rows
self.cols = cols
self.kanaele = kanaele
@@ -51,15 +51,15 @@ class Dyschromasie:
def Simulate(self):
removeGammaCorrectionLUT = createGammaLookup()
if self.sim_kind == 'p':
if self.sim_kind == 'Protanop':
sim_mat = np.array([[(1 - self.sim_faktor), 1.05118294 * self.sim_faktor, -0.05116099 * self.sim_faktor],
[0, 1, 0],
[0, 0, 1]])
elif self.sim_kind == 'd':
elif self.sim_kind == 'Deuteranop':
sim_mat = np.array([[1, 0, 0],
[0.9513092 * self.sim_faktor, (1 - self.sim_faktor), 0.04866992 * self.sim_faktor],
[0, 0, 1]])
else:
elif self.sim_kind == 'Tritanop':
sim_mat = np.array([[1, 0, 0],
[0, 1, 0],
[-0.86744736 * self.sim_faktor, 1.86727089 * self.sim_faktor, (1 - self.sim_faktor)]])
@@ -97,22 +97,22 @@ class Dyschromasie:
for x in range(3):
E[i, j, x] = abs(int(self.img_mat[i, j, x]) - int(simulated_image[i, j, x]))
ERR = np.zeros_like(image).astype('int32')
ERR = np.zeros_like(self.img_mat).astype('int32')
for i in range(self.rows):
for j in range(self.cols):
err = E[i, j, :3]
ERR[i, j, :3] = np.dot(err2mod, err)
dtpn = np.copy(image).astype('int32')
dtpn = np.copy(self.img_mat).astype('int32')
for i in range(self.rows):
for j in range(self.cols):
for x in range(3):
dtpn[i, j, x] = abs(int(ERR[i, j, x]) + int(image[i, j, x]))
dtpn[i, j, x] = abs(int(ERR[i, j, x]) + int(self.img_mat[i, j, x]))
for i in range(rows):
for j in range(cols):
for i in range(self.rows):
for j in range(self.cols):
dtpn[i, j, 0] = max(0, dtpn[i, j, 0])
dtpn[i, j, 0] = min(255, dtpn[i, j, 0])
dtpn[i, j, 1] = max(0, dtpn[i, j, 1])
@@ -125,16 +125,3 @@ class Dyschromasie:
dalt = Dyschromasie(result, self.rows, self.cols, self.kanaele, self.sim_faktor, self.sim_kind)
return dalt.Simulate()
def main():
script_dir = sys.path[0]
path = script_dir[:-4] + r'Beispielbilder\rot-gruen-schwaeche-test-bild.jpg'
image = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2RGB)
rows, cols, kanaele = image.shape
dalt = Dyschromasie(image, rows, cols, kanaele, 1, 'p')
cv2.imshow('Dalt_Img', cv2.cvtColor(dalt.daltonize(), cv2.COLOR_RGB2BGR))
cv2.waitKey(0)
# main()

BIN
Code/__pycache__/Farbaenderung.cpython-38.pyc View File


Loading…
Cancel
Save