OpenCVTutorial/Contour_ShapeDetection.py at master · sanketkar24/OpenCVTutorial · 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
import cv2
import numpy as np
def stackImages(scale, imgArray):
    rows = len(imgArray)
    cols = len(imgArray[0])
    rowsAvailable = isinstance(imgArray[0], list)
    width = imgArray[0][0].shape[1]
    height = imgArray[0][0].shape[0]
    if rowsAvailable:
        for x in range(0, rows):
            for y in range(0, cols):
                if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
                else:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),
                                                None, scale, scale)
                if len(imgArray[x][y].shape) == 2: imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)
        imageBlank = np.zeros((height, width, 3), np.uint8)
        hor = [imageBlank] * rows
        hor_con = [imageBlank] * rows
        for x in range(0, rows):
            hor[x] = np.hstack(imgArray[x])
        ver = np.vstack(hor)
    else:
        for x in range(0, rows):
            if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
                imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
            else:
                imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None, scale, scale)
            if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
        hor = np.hstack(imgArray)
        ver = hor
    return ver

def getContours(img):
    contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
    for cnt in contours:
        area = cv2.contourArea(cnt)
        print(area)
        if area>500:
            cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
            peri = cv2.arcLength(cnt,True)
            #print(peri)
            approx = cv2.approxPolyDP(cnt, 0.02*peri, True)
            print(len(approx))
            objCor = len(approx)
            x ,y ,w ,h= cv2.boundingRect(approx)

            if objCor ==3: objectType = "Tri"
            elif objCor ==4:
                aspRatio = w/(float(h))
                if aspRatio >0.95 and aspRatio<1.05:
                    objectType = "Square"
                else: objectType="Rectangle"
            elif objCor>4: objectType = "Circles"
            else: objectType = "None"

            cv2.rectangle(imgContour,(x,y),(x+w, y+h), (0,255,0),2)
            cv2.putText(imgContour, objectType, (x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX, 0.7, (0,0,0),2)

path = 'resources/shapes.png'
img = cv2.imread(path)
imgContour = img.copy()

imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray, (7,7), 1)
imgCanny = cv2.Canny(imgBlur, 50, 50)
getContours(imgCanny)
imgBlank = np.zeros_like(img)

imgStack = stackImages(0.8, ([img,imgGray,imgBlur],
                             [imgCanny,imgContour,imgBlank]))

cv2.imshow("Stack", imgStack)
cv2.waitKey(0)