opencvKCF/loopdetector.py at master · CHONSPQX/opencvKCF · 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
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
# coding:utf-8
import math
import cv2
from matplotlib import pyplot as plt
from test import *
import numpy as np


def lodetector(img):
    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    edges = cv2.Canny(img_gray, 100, 200)
    _, bi_img = cv2.threshold(img_gray, 100, 255, cv2.THRESH_BINARY)
    img_fc, contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    hierarchy = hierarchy[0]
    found = set()
    for i in range(len(contours)):
        k = i
        c = 0
        while hierarchy[k][2] != -1:
            k = hierarchy[k][2]
            c = c + 1
        if c >= 2:
            found.add((i,c))
    try:
        found_max=max(found,key=lambda i:i[1])[0]
        print found
        rect = cv2.minAreaRect(contours[found_max])
        box = cv2.boxPoints(rect)
        box = np.array(box)
        Xs = [i[0] for i in box]
        Ys = [i[1] for i in box]
        x1 = min(Xs)
        x2 = max(Xs)
        y1 = min(Ys)
        y2 = max(Ys)
        hight = y2 - y1
        width = x2 - x1
        print x1,y1,width,hight
    except BaseException:
        x1=y1=width=hight=1
    return x1, y1, width, hight


def all(img_name, resize_flag=False):
    print img_name
    img = cv2.imread(img_name)
    # print img.shape
    if resize_flag:
        img = imgresize(img,3)
    # print img.shape
    # cv2.imshow("img",img)
    # cv2.waitKey(0)
    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # cv2.imshow("img_gray",img_gray)
    # cv2.waitKey(0)
    img_gb = cv2.GaussianBlur(img_gray, (5, 5), 0)
    # cv2.imshow("img_gb",img_gb)
    # cv2.waitKey(0)
    edges = cv2.Canny(img_gray, 100, 200)
    # cv2.imshow("edges",edges)
    # cv2.waitKey(0)
    _, bi_img = cv2.threshold(img_gray, 100, 255, cv2.THRESH_BINARY)
    # print bi_img
    # cv2.imshow("bi_img",bi_img)

    img_fc, contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    # print
    hierarchy = hierarchy[0]
    # print len(contours)
    found = set()
    layer = []
    for i in range(len(contours)):
        k = i
        c = 0
        while hierarchy[k][2] != -1:
            # print hierarchy[k]
            # print hierarchy[k][2]
            # print hierarchy[k][0]
            k = hierarchy[k][2]
            c = c + 1
        layer.append((i, c))
        if c >= 4:
            found.add(i)

    ffound = set()

    for i in found:
        for j in found:
            if i == j:
                continue
            if (hierarchy[j][2] == i):
                ffound.add(i)

    found = found - ffound

    found = list(found)

    layer = np.array(layer)

    # for i in found:
    #     img_dc = img.copy()
    #     cv2.drawContours(img_dc, contours, i, (0, 255, 0), 3)
    #     cv2.imshow("img"+str(i),img_dc)
    #     cv2.waitKey(0)

    draw_img = img.copy()

    for i in found:
        rect = cv2.minAreaRect(contours[i])
        box = cv2.boxPoints(rect)
        box = np.int0(box)
        cv2.drawContours(draw_img, [box], 0, (0, 0, 255), 2)

    # cv2.imshow("draw_img",draw_img)
    # cv2.waitKey(0)

    boxes = []
    for i in found:
        rect = cv2.minAreaRect(contours[i])
        box = cv2.boxPoints(rect)
        box = np.int0(box)
        box = map(tuple, box)
        # print box
        boxes.append(box)

    print "boxes.num: " + str(len(boxes))

    valid = set()

    for i in range(len(boxes)):
        for j in range(i + 1, len(boxes)):
            if mycheck(boxes[i], boxes[j], img_gray, contours, i, j):
                valid.add(i)
                valid.add(j)

    # cv2.imshow("line",draw_img)
    # cv2.waitKey(0)
    # print bi_img


    print "valid: ", valid

    contour_all = []
    while len(valid) > 0:
        c = valid.pop()
        # print c
        for point in boxes[c]:
            contour_all.append(point)
    contour_all = np.array(contour_all)
    # print contour_all.shape

    rect = cv2.minAreaRect(contour_all)
    box = cv2.boxPoints(rect)
    box = np.array(box)
    draw_img = img.copy()
    # cv2.polylines(draw_img, np.int32([box]), True, (0, 0, 255), 3)
    # cv2.imshow("outcome", draw_img)
    # cv2.waitKey(0)


# all('1.jpg')
# all('2.jpg', True)
# all('3.jpg')
# all('6.jpg',1)
# all('5.jpg',True)
# cv2.waitKey(0)