ハフ変換のforループによる複数枚の処理

前提・実現したいこと

for文で複数枚の画像をハフ変換するプログラムで、下記のエラーが出て困っています。
このエラーはどういった内容なのでしょうか。また解決方法を教えていただきたいです。よろしくお願いいたします。

発生している問題・エラーメッセージ

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
AttributeError: 'NoneType' object has no attribute 'rint'

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
<ipython-input-18-169dfba55118> in <module>
    117     img_ga = cv2.GaussianBlur(inv,(5,5),0)
    118     circles = cv2.HoughCircles(img_ga.astype(np.uint8),cv2.HOUGH_GRADIENT,1,50,param1=10,param2=20,minRadius=5,maxRadius=80)
--> 119     circles = np.uint16(np.around(circles))
    120     for i in circles[0,:]:
    121         cv2.circle(inv,(i[0],i[1]),i[2],(0,255,0),2)

<__array_function__ internals> in around(*args, **kwargs)

~\anaconda3\lib\site-packages\numpy\core\fromnumeric.py in around(a, decimals, out)
   3222 
   3223     """
-> 3224     return _wrapfunc(a, 'round', decimals=decimals, out=out)
   3225 
   3226 

~\anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
     56     bound = getattr(obj, method, None)
     57     if bound is None:
---> 58         return _wrapit(obj, method, *args, **kwds)
     59 
     60     try:

~\anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapit(obj, method, *args, **kwds)
     45     except AttributeError:
     46         wrap = None
---> 47     result = getattr(asarray(obj), method)(*args, **kwds)
     48     if wrap:
     49         if not isinstance(result, mu.ndarray):

TypeError: loop of ufunc does not support argument 0 of type NoneType which has no callable rint method

該当のソースコード

python
1for i in range (1550,1560):
2
3    img = cv2.imread('DSC0'+str(i)+'.jpg',0)
4    height = img.shape[0]
5    width = img.shape[1]
6    resize_img = cv2.resize(img,(int(width*0.5),int(height*0.5)))
7
8    #ganma
9    img_blur = cv2.GaussianBlur(resize_img,(499,499),0)
10    height = img_blur.shape[0]
11    width = img_blur.shape[1]
12    np.clip(height, 1,254)
13    np.clip(width,1,254)
14    b = img_blur/255.0
15    g = np.log(0.5)/np.log(b)
16    img2 = 255.0*np.power(resize_img/255.0,g)
17    cv2.imwrite('ganma-'+str(i)+'.jpg',img2)
18
19    #contrast
20    img3 = cv2.imread('ganma-'+str(i)+'.jpg',0)
21    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
22    cl2 = clahe.apply(img3.astype(np.uint8))
23    cv2.imwrite('cl-'+str(i)+'.jpg',cl2)
24
25    #threshold
26    threshold = 100
27    ret, img_thresh = cv2.threshold(cl1, threshold, 255, cv2.THRESH_BINARY)
28    cv2.imwrite('th-'+str(i)+'.jpg', img_thresh)
29
30    #morphology
31    kernel = np.ones((5,5),np.uint8)
32    closing = cv2.morphologyEx(img_thresh,cv2.MORPH_CLOSE,kernel)
33    cv2.imwrite('mor-'+str(i)+'.jpg',closing)
34    frontimg = closing
35    
36    #Background subtraction
37    fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
38    fgmask = fgbg.apply(backimg)
39    fgmask = fgbg.apply(frontimg)
40    cv2.imwrite('front-'+str(i)+'.jpg',fgmask)
41
42    #remove
43    def remove_objects(img, lower_size=None, upper_size=None):
44        nlabels, labels, stats, centroids = cv2.connectedComponentsWithStats(img)
45        sizes = stats[1:, -1]
46        _img = np.zeros((labels.shape))
47        for i in range(1, nlabels):
48            if (lower_size is not None) and (upper_size is not None):
49                if lower_size < sizes[i - 1] and sizes[i - 1] < upper_size:
50                    _img[labels == i] = 255
51            elif (lower_size is not None) and (upper_size is None):
52                if lower_size < sizes[i - 1]:
53                    _img[labels == i] = 255
54            elif (lower_size is None) and (upper_size is not None):
55                if sizes[i - 1] < upper_size:
56                    _img[labels == i] = 255
57        return _img
58    #org_img= cv2.imread('front-'+str(i)+'.jpg',0)
59    img_remove = remove_objects(fgmask,lower_size=50, upper_size=None)    
60    cv2.imwrite('remove-'+str(i)+'.jpg',img_remove)
61
62    #inversion
63    inv = cv2.bitwise_not(img_remove)
64
65    #haugh
66    wb = excel.Workbook()
67    ws = wb.active
68    ws['A1'] = "width"
69    ws['B1'] = "height"
70    ws['C1'] = "r-pixel"
71    ws['D1'] = "d-pixel"
72    ws['E1'] = "r-μm"
73    ws['F1'] = "d-μm"
74    ws['G1'] = "area-μm"
75    ws.title = "Sheet_1"
76    img_ga = cv2.GaussianBlur(inv,(5,5),0)
77    circles = cv2.HoughCircles(img_ga.astype(np.uint8),cv2.HOUGH_GRADIENT,1,50,param1=10,param2=20,minRadius=5,maxRadius=80)
78    circles = np.uint16(np.around(circles))
79    for i in circles[0,:]:
80        cv2.circle(inv,(i[0],i[1]),i[2],(0,255,0),2)
81        cv2.circle(inv,(i[0],i[1]),2,(0,0,255),3)
82
83        ws.append((float(i[0]), float(i[1]),float(i[2]),float(i[2]*2),float(i[2]*41.1*pow(10,-3)),float(i[2]*2*41.1*pow(10,-3)),float((i[2]*41.1)*(i[2]*41.1)*math.pi)))
84  
85        wb.save(r"hahu"+str(i)+".xlsx")
86    
87    cv2.imwrite('hahu'+str(i)+'.jpg',inv)

行動規範の内容に同意します

回答1件

ベストアンサー

cv2.HoughCircles() はハフ変換に失敗した際空の配列ではなく None を返すようです。ですので None を array([[[]]]) に変換してしまうか、その処理を飛ばしてしまうか、もしくはパラメーターをチューニングしてハフ変換を失敗しないようにするかしましょう（最後の手法は専門家ではないのでわかんないっす！）。

投稿2021/01/12 07:15