ハフ変換での_src.type() == CV_8UC1のエラー対処方法について

Question

前提・実現したいこと

前回の質問と同じような内容です。
ハフ変換を行う際に、前処理の結果を引き継いで処理したいです。
何か方法があれば教えていただけますでしょうか。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

error                                     Traceback (most recent call last)
<ipython-input-16-59ad1902ff98> in <module>
    116     ws.title = "Sheet_1"
    117     img_ga = cv2.GaussianBlur(inv,(5,5),0)
--> 118     circles = cv2.HoughCircles(img_ga,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,:]:

error: OpenCV(4.4.0) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-71670poj\opencv\modules\imgproc\src\hough.cpp:2253: error: (-215:Assertion failed) !_image.empty() && _image.type() == CV_8UC1 && (_image.isMat() || _image.isUMat()) in function 'cv::HoughCircles'

該当のソースコード

  img = cv2.imread('DSC0'+str(i)+'.jpg',0)
    height = img.shape[0]
    width = img.shape[1]
    resize_img = cv2.resize(img,(int(width*0.5),int(height*0.5)))

    #ganma
    img_blur = cv2.GaussianBlur(resize_img,(499,499),0)
    height = img_blur.shape[0]
    width = img_blur.shape[1]
    np.clip(height, 1,254)
    np.clip(width,1,254)
    b = img_blur/255.0
    g = np.log(0.5)/np.log(b)
    img2 = 255.0*np.power(resize_img/255.0,g)
    cv2.imwrite('ganma-'+str(i)+'.jpg',img2)

    #contrast
    img3 = cv2.imread('ganma-'+str(i)+'.jpg',0)
    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
    cl2 = clahe.apply(img3.astype(np.uint8))
    cv2.imwrite('cl-'+str(i)+'.jpg',cl2)

    #threshold
    threshold = 100
    ret, img_thresh = cv2.threshold(cl1, threshold, 255, cv2.THRESH_BINARY)
    cv2.imwrite('th-'+str(i)+'.jpg', img_thresh)

    #morphology
    kernel = np.ones((5,5),np.uint8)
    closing = cv2.morphologyEx(img_thresh,cv2.MORPH_CLOSE,kernel)
    cv2.imwrite('mor-'+str(i)+'.jpg',closing)
    frontimg = closing
    
    #Background subtraction
    fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
    fgmask = fgbg.apply(backimg)
    fgmask = fgbg.apply(frontimg)
    cv2.imwrite('front-'+str(i)+'.jpg',fgmask)

    #remove
    def remove_objects(img, lower_size=None, upper_size=None):
        nlabels, labels, stats, centroids = cv2.connectedComponentsWithStats(img)
        sizes = stats[1:, -1]
        _img = np.zeros((labels.shape))
        for i in range(1, nlabels):
            if (lower_size is not None) and (upper_size is not None):
                if lower_size < sizes[i - 1] and sizes[i - 1] < upper_size:
                    _img[labels == i] = 255
            elif (lower_size is not None) and (upper_size is None):
                if lower_size < sizes[i - 1]:
                    _img[labels == i] = 255
            elif (lower_size is None) and (upper_size is not None):
                if sizes[i - 1] < upper_size:
                    _img[labels == i] = 255
        return _img
    #org_img= cv2.imread('front-'+str(i)+'.jpg',0)
    img_remove = remove_objects(fgmask,lower_size=50, upper_size=None)    
    cv2.imwrite('remove-'+str(i)+'.jpg',img_remove)

    #inversion
    inv = cv2.bitwise_not(img_remove)

    #haugh
    wb = excel.Workbook()
    ws = wb.active
    ws['A1'] = "width"
    ws['B1'] = "height"
    ws['C1'] = "r-pixel"
    ws['D1'] = "d-pixel"
    ws['E1'] = "r-μm"
    ws['F1'] = "d-μm"
    ws['G1'] = "area-μm"
    ws.title = "Sheet_1"
    img_ga = cv2.GaussianBlur(inv,(5,5),0)
    circles = cv2.HoughCircles(img_ga,cv2.HOUGH_GRADIENT,1,50,param1=10,param2=20,minRadius=5,maxRadius=80)
    circles = np.uint16(np.around(circles))
    for i in circles[0,:]:
        cv2.circle(inv,(i[0],i[1]),i[2],(0,255,0),2)
        cv2.circle(inv,(i[0],i[1]),2,(0,0,255),3)

        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)))
  
        wb.save(r"hahu"+str(i)+".xlsx")
    
    cv2.imwrite('hahu'+str(i)+'.jpg',inv)

試したこと

とりあえずハフ変換の部分を前回の質問での回答を参考に

circles = cv2.HoughCircles(img_ga.astype(np.unit8),cv2.HOUGH_GRADIENT,1,50,param1=10,param2=20,minRadius=5,maxRadius=80)

としたところ
AttributeError: module 'numpy' has no attribute 'unit8'
とエラーが出てしまい頓挫しています。

Comments

[jbpb0]

> AttributeError: module 'numpy' has no attribute 'unit8'

unit8 → uint8
これだけで直るかは分からないけど

Answer 1

× unit8
○ uint8

Comments

[gomsis]

あ、ありがとうございます。。。