Erster Daltonizationalgorithmus

Code/Farbaenderung.py

@@ -1,7 +1,6 @@
 import numpy as np
 import cv2
-
+import sys
-
 
 def createGammaLookup():
     return np.array([removeGammaCorrection(i) for i in np.arange(0, 256)]).astype("float64")
@@ -87,3 +86,47 @@ class Dyschromasie:
 
         return self.sim_image
 
+
+script_dir = sys.path[0]
+path = script_dir[:-4] + "Beispielbilder\Fall_trees.jpg"
+image = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2RGB)
+
+rows, cols, kanaele = image.shape
+
+p = Dyschromasie(image, rows, cols, kanaele, 1, 'p')
+
+simulated_image = p.Simulate()
+
+E = np.copy(simulated_image)
+for i in range(rows):
+    for j in range(cols):
+        for x in range(3):
+            E[i, j, x] = abs(int(simulated_image[i, j, x]) - int(image[i, j, x]))
+
+ERR = np.zeros_like(image)
+
+err2mod = np.array([[0,0,0],[0.7,1,0],[0.7,0,1]])
+
+for i in range(rows):
+    for j in range(cols):
+        err = E[i,j,:3]
+        ERR[i,j,:3] = np.dot(err2mod, err)
+
+dtpn = np.copy(image)
+
+for i in range(rows):
+    for j in range(cols):
+        for x in range(3):
+            dtpn[i, j, x] = (int(ERR[i, j, x]) + int(image[i, j, x]))
+
+for i in range(rows):
+    for j in range(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])
+        dtpn[i, j, 1] = min(255, dtpn[i, j, 1])
+        dtpn[i,  j, 2] = max(0, dtpn[i, j, 2])
+        dtpn[i, j, 2] = min(255, dtpn[i, j, 2])
+
+cv2.imshow('Dalt_Img', cv2.cvtColor(dtpn, cv2.COLOR_RGB2BGR))
+cv2.waitKey(0)