SponselMa71420/Projekt_Dyschromasie
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Fehler im Algorithmus gefunden

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Anders als im Paper werden die RGB Werte nicht in der Reihenfolge Rot Grün Blau (RGB), sondern in OpenCV als Blau grün rot (BGR) abgespeichert.
Also ist ein e Funktion zum "Umdrehen" der Matrix nötig!
This commit is contained in:
Max Sponsel 2020-07-09 16:06:12 +02:00
parent 899580b119
commit e7eead37ee
2 changed files with 11 additions and 14 deletions
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18
.idea/workspace.xml generated
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@ -77,28 +77,28 @@
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<SUITE FILE_PATH="coverage/Projekt_Dyschromasie$Dyschromasie.coverage" NAME="Dyschromasie Coverage Results" MODIFIED="1593693827197" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/Code" />
<SUITE FILE_PATH="coverage/Projekt_Dyschromasie$Dyschromasie.coverage" NAME="Dyschromasie Coverage Results" MODIFIED="1594303176426" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/Code" />
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7
Code/Dyschromasie.py
View File

@ -3,6 +3,7 @@ import tkinter # Zum Erstellen von GUIs
import numpy as np # Numpy Import
import sys
# Einlesen des Bildes
script_dir = sys.path[0]
path = script_dir[:-4] + "Beispielbilder\grocery_store.jpg"
@ -12,7 +13,6 @@ rows = image.shape[0] # Auslesen der Zeilenanzahl
cols = image.shape[1] # Auslesen der Spaltenanzahl
kanaele = image.shape[2] # Auslesen der Kanaele (3 fuer RGB, 1 fuer Graubild)
def gammaCorrection(v):
if v <= 0.04045 * 255:
return float(((v / 255) / 12.92))
@ -62,8 +62,6 @@ T_reversed = np.array([[5.47221206, -4.6419601, 0.16963708],
[-1.1252419, 2.29317094, -0.1678952],
[0.02980165, -0.19318073, 1.16364789]])
# Simulationsmatrizen fuer Protanop
S_p = np.array([[0, 1.05118294, -0.05116099], #Simulationsmatrix fuer Protanopie
[0, 1, 0],
[0, 0, 1]])
@ -80,7 +78,7 @@ S_t = np.array([[1, 0, 0], #Simulationsmatrix fuer Tritanopi
#Multiplikation der einzelnen Pixel
for i in range(rows):
for j in range(cols):
cb_image[i,j] = T_reversed.dot(S_p).dot(T).dot(cb_image[i,j])
cb_image[i,j] = T_reversed.dot(S_p).dot(T).dot(cb_image[i,j]) #ToDo Statt RBG ist noch BGR
sim_image = np.copy(cb_image)
sim_image = sim_image.astype('uint8')
@ -91,7 +89,6 @@ for i in range(rows):
for x in range(3):
sim_image[i, j, x] = reverseGammaCorrection(cb_image[i, j, x])
cv2.namedWindow("Display") # Displaywindow erstellen
cv2.imshow("Display", sim_image) # Bild zeigen
cv2.waitKey(0) # Fenster offen halten