From b53df627ba27987e7ecba22c75dcf67f1dbee21a Mon Sep 17 00:00:00 2001
From: Yacine Benouniche <yacine.benouniche@polymtl.ca>
Date: Sat, 24 Nov 2018 13:35:19 -0500
Subject: [PATCH] boundaryTracing update

---
 Projet/BoundaryTracing/BoudaryTracing.py | 95 +++++++++++++++---------
 1 file changed, 61 insertions(+), 34 deletions(-)

diff --git a/Projet/BoundaryTracing/BoudaryTracing.py b/Projet/BoundaryTracing/BoudaryTracing.py
index 5d242bf..f4b4239 100644
--- a/Projet/BoundaryTracing/BoudaryTracing.py
+++ b/Projet/BoundaryTracing/BoudaryTracing.py
@@ -1,85 +1,112 @@
 import math
+import numpy as np
 
 WHITE_PIXEL = 255
-
+BLACK_PIXEL = 0
 
 class BoundaryTracing:
-    def __init__(self, image):
-        self.image = image
+    def __init__(self):
+        self.image = None
+        self.minx = None
+        self.maxx = None
+        self.miny = None
+        self.maxy = None
         self.initial_trace_point = (0, 0)
+        self.UD = 0
+        self.LR = 0
+
+    def run(self, image):
+        self.image = image
         self.minx = self.calcul_minx()
         self.maxx = self.calcul_maxx()
         self.miny = self.calcul_miny()
         self.maxy = self.calcul_maxy()
-        self.optimal_y = 0
-        self.UD = 0
-        self.LR = 0
-
-    def run(self):
-        self.optimal_y = self.optimal_y_level()
         self.initial_trace_direction()
+        self.trace()
+        self.flush()
 
-    def optimal_y_level(self):
-        dy = self.maxy - self.miny
-        optimaly = math.floor(0.33 * dy)
-        return optimaly
+    def flush(self):
+        self.image = None
+        self.minx = None
+        self.maxx = None
+        self.miny = None
+        self.maxy = None
+
+    # def optimal_y_level(self):
+    #     print(self.maxy)
+    #     print(self.miny)
+    #     dy = self.maxy - self.miny
+    #     optimaly = math.floor(0.33 * dy)
+    #     return optimaly
 
     def initial_trace_direction(self):
         self.initial_trace_point = (0, 0)
-        for i in range(0, len(self.image[self.optimal_y])):
-            if len(self.image[self.optimal_y][i]) == WHITE_PIXEL:
-                self.initial_trace_point = (i, self.optimal_y)
+        for i in range(self.minx, self.maxx):
+            if self.image[self.maxy][i] != BLACK_PIXEL:
+                self.initial_trace_point = (i, self.maxy)
                 break
         x = self.initial_trace_point[0]
         y = self.initial_trace_point[1]
         self.UD = 1
-        while y < self.miny and self.image[y][x] == WHITE_PIXEL:
+        while y >= self.miny and self.image[y][x] != BLACK_PIXEL:
             y = y - 1
         if y > 0 and x < len(self.image[y]):
-            if self.image[y][x+1] == WHITE_PIXEL or self.image[y-1][x+1]:
-                self.LR = -1
-        if y > 0 and x > 0:
-            if self.image[y][x-1] == WHITE_PIXEL or self.image[y-1][x-1]:
+            if self.image[y][x+1] != BLACK_PIXEL or self.image[y-1][x+1]:
                 self.LR = 1
+        if y > 0 and x > 0:
+            if self.image[y][x-1] != BLACK_PIXEL or self.image[y-1][x-1]:
+                self.LR = -1
 
     def trace(self):
         x = self.initial_trace_point[0]
         y = self.initial_trace_point[1]
         count = 0
+        print(x, ' ', y, ' ', self.LR, ' ', self.UD)
+
+        mask = np.zeros((len(self.image), len(self.image[0])))
+        while x != self.maxx:
+            if self.UD == 1:
+                y = y - 1
+            elif self.UD == -1:
+                y = y + 1
+
+            if self.LR == 1 and self.image[y][x+1] != BLACK_PIXEL:
+                x = x + 1
+            elif self.LR == -1 and self.image[y][x-1] != BLACK_PIXEL:
+                x = x - 1
 
     def calcul_minx(self):
         minx = 0
-        for i in range(0, len(self.image[0])):
-            for j in range(0, len(self.image)):
-                if self.image[j][i] == WHITE_PIXEL:
+        for i in range(1, len(self.image[0]) - 1):
+            for j in range(1, len(self.image) - 1):
+                if self.image[j][i] != BLACK_PIXEL:
                     minx = i
                     return minx
         return minx
 
     def calcul_maxx(self):
         maxx = 0
-        for i in range(len(self.image[0]), 0, -1):
-            for j in range(0, len(self.image)):
-                if self.image[j][i] == WHITE_PIXEL:
+        for i in range(len(self.image[0]) - 1, 0, -1):
+            for j in range(1, len(self.image) - 1):
+                if self.image[j][i] != BLACK_PIXEL:
                     maxx = i
                     return maxx
         return maxx
 
-
     def calcul_miny(self):
         miny = 0
-        for i in range(0, len(self.image)):
-            for j in range(0, len(self.image[i])):
-                if self.image[i][j] == WHITE_PIXEL:
+        for i in range(1, len(self.image) - 1):
+            for j in range(1, len(self.image[i]) - 1):
+                if self.image[i][j] != BLACK_PIXEL:
                     miny = i
                     return miny
         return miny
 
     def calcul_maxy(self):
         maxy = 0
-        for i in range(len(self.image), 0, -1):
-            for j in range(0, len(self.image[i])):
-                if self.image[i][j] == WHITE_PIXEL:
+        for i in range(len(self.image) - 2, 0, -1):
+            for j in range(1, len(self.image[i]) - 1):
+                if self.image[i][j] != BLACK_PIXEL:
                     maxy = i
                     return maxy
         return maxy