Dijkstra-optimization-algorithm-implementation/testpath1.py at main · sivasthigan1999/Dijkstra-optimization-algorithm-implementation · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
import numpy as np
import cv2

img = cv2.imread(r"C:\Users\Sivasthigan\PycharmProjects\droneproject\1.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, threshold = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
cv2.bitwise_not(threshold, threshold)
contours, hierarchy = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
listx = []
listy = []
point=[]
points = []
lst_sort=[]

value = {}
megalist=[]


lst_coordinates=[]
fx = 0
fy = 0
index=0
w=0

for i in range(0, len(contours)):

    c = contours[i]
    size = cv2.contourArea(c)
    if size > 11:
        M = cv2.moments(c)
        cX = int(M["m10"] / M["m00"])
        cY = int(M["m01"] / M["m00"])
        points.append([cX,cY])

        cv2.circle(img, (fx, fy), 5, (255, 0, 0), 10)
        cv2.circle(img, (cX, cY), 5, (255, 0, 0), 10)
dictlis=[]
for p in range(len(points)):
    dictlis.append([p+1,points[p]])
print(dictlis)


for i in range(len(points)):

    graph = {}

    print('points',points)
    print('dictlis',dictlis)
    for j in points:

        points1 = {}
        Pathdistance = np.sqrt((fx-j[0]) ** 2 + (fy - j[1]) ** 2)
        #print('2nd time', fx, fy)
        #print("fidtance of first path", Pathdistance)
        points1['cX']=j[0]
        points1['cY']=j[1]
        points1['Pathdistance']=Pathdistance
        lst_coordinates.append(points1)
        #print(points1)
    print(lst_coordinates)
    #print(points1)


    for k in lst_coordinates:
        lst_sort.append(k['Pathdistance'])
    lst_sort.sort()
    max_fp_dstance = min(lst_sort)
    #print(lst_sort)


    for z in range(len(dictlis)):
        graph[str(dictlis[z][0])] =lst_coordinates[z]['Pathdistance']

    print('graph',graph)

    #megalist.append(graph)
    #print('mega',megalist)
    x = 0
    for t in lst_coordinates:
        # xx = i['cX']
        # yy = i['cY']
        # point.append([xx,yy])
        # print(point)
        index = index + 1
        for k, v in t.items():
            if (t[k] == max_fp_dstance):
                mX = t['cX']
                mY = t['cY']
                x = index
                break
        if (index == x):
            break
    fx=mX
    fy=mY

    value[str(w)] = graph
    for q in range (len(dictlis)):
        if dictlis[q][1]==[fx,fy]:

            #q=q+1
            #print(q)
            w=dictlis[q][0]
            print(w)
            break


    print(fx,fy)
    lst_coordinates.clear()
    lst_sort.clear()
    points.remove([fx,fy])
    dictlis.remove([w,[fx,fy]])
    #graph.clear()

print(value)