如何解决错误 UnboundLocalError: local variable 'max_contour'赋值前引用

Question

Hello everyone I hope you are doing well I have implemented the following code. 这是我的数据集 https://drive.google.com/drive/folders/1ARQLty-f7i_W6fvvcIx-3VUUzjb3o1KX?usp=sharing

I read the dicom files from the folder and apply some preprocessing to it to the segment area.我开发了一个分割区域的函数，但是我收到以下错误 I got the following error when I run the code

How can I solve that

UnboundLocalError: local variable 'max_contour' referenced before assignment

from matplotlib.pyplot import imshow
import matplotlib.pyplot as plt
import pydicom
import numpy
import tkinter
from tkinter import filedialog
import os
import numpy as np
import pydicom as dcm
import cv2
def window_image(img, window_center,window_width, intercept, slope, rescale=True):
    img = (img*slope +intercept) #for translation adjustments given in the dicom file. 
    img_min = window_center - window_width//2 #minimum HU level
    img_max = window_center + window_width//2 #maximum HU level
    img[img<img_min] = img_min #set img_min for all HU levels less than minimum HU level
    img[img>img_max] = img_max #set img_max for all HU levels higher than maximum HU level
    if rescale: 
     img = (img - img_min) / (img_max - img_min)*255.0 
    return img

def preprocess_dicom(img,outdir,image_path):
    ht, wd = img.shape[:2]

    # convert to grayscale
    #gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    # threshold
    thresh = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]

    # get external contours
    contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    #contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours = contours[0] if len(contours) == 2 else contours[1]
    
    max_aspect=0
    for cntr in contours:
        x,y,w,h = cv2.boundingRect(cntr)
        aspect = w/h
        if aspect > max_aspect:
            max_aspect = aspect
            max_contour = cntr
    
    # create mask from max_contour
    mask = np.zeros((ht,wd), dtype=np.uint8)
    mask = cv2.drawContours(mask, [max_contour], 0, (255), -1)

    # dilate mask
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
    mask = cv2.morphologyEx(mask, cv2.MORPH_DILATE, kernel)

    # invert mask
    mask = 255 - mask

    # mask out region in input
    result = img.copy()
    result = cv2.bitwise_and(result, result, mask=mask)

    # save resulting image
     # Open the outlined image
    fig, ax = plt.subplots(1,2)
    ax[0].imshow(img,'gray');
    ax[1].imshow(result,'gray');
    cv2.imwrite(os.path.join(outdir,os.path.basename(image_path).replace(".dcm", "_segment.png")), result)
    return result  

def get_first_of_dicom_field_as_int(x):
    #get x[0] as in int is x is a 'pydicom.multival.MultiValue', otherwise get int(x)
    if type(x) == dcm.multival.MultiValue: return int(x[0])
    else: return int(x)
    
def get_windowing(data):
    dicom_fields = [data[('0028','1050')].value, #window center
                    data[('0028','1051')].value, #window width
                    data[('0028','1052')].value, #intercept
                    data[('0028','1053')].value] #slope
    return [get_first_of_dicom_field_as_int(x) for x in dicom_fields]






root=tkinter.Tk()
root.withdraw()

currdir=os.getcwd()
PathDicom=filedialog.askdirectory(parent=root,initialdir=currdir,title='Please select a folder with DICOM')

if len (PathDicom)>0:
    print(("You chose %s")%PathDicom)
    
lstFilesDCM=[]
for dirName,subdirList,fileList in os.walk(PathDicom):
    for filename in fileList:
        if ".dcm" in filename.lower():
            lstFilesDCM.append(os.path.join(dirName,filename))
RefDs=pydicom.dcmread(lstFilesDCM[0])
ConstPixelDims=(int(RefDs.Rows),int(RefDs.Columns),len(lstFilesDCM))
cal=RefDs.RescaleIntercept
ArrayDicom=numpy.zeros(ConstPixelDims,dtype=RefDs.pixel_array.dtype)
ind = 0 
folder_name=r'C:\Users\Hammad\Desktop'
for i in lstFilesDCM:
    for j in range(1, len(lstFilesDCM)):
        ds=pydicom.dcmread(i)
        ArrayDicom[:,:,lstFilesDCM.index(i)]=ds.pixel_array
        
        window_center , window_width, intercept, slope = get_windowing(ds)
        output = window_image(ArrayDicom[:,:,j], window_center, window_width, intercept, slope)
        imshow(output,cmap='gray')
        output = output - np.min(output)
        output = output / np.max(output)
        output = (output * 255).astype(np.uint8)
        imgsegment=preprocess_dicom(output,r'C:\Users\Hammad\Desktop\manifest-1643119746471\manifest-1645243048125\CPTAC-SAR',i)
        RefDs.PixelData = imgsegment.tobytes()
        RefDs.save_as( folder_name+ '/{0}.dcm'.format(ind))    
        ind = ind+1

Can anybody please help me in this

Answer 1

for cntr in contours:
    x,y,w,h = cv2.boundingRect(cntr)
    aspect = w/h
    if aspect > max_aspect:
        max_aspect = aspect
        max_contour = cntr

这是代码中定义 max_contour 的唯一位置。因此，如果您收到该错误，则一定意味着 max_contour = cntr 代码行从未执行过。

这可能是由于 contours 为空，或者 aspect > > 造成的。 max_aspect 始终为 false。

Answer 2

max_contour 似乎是在 for 循环中首先定义的，但是您在 for 循环之外使用它 (mask = cv2.drawContours(mask, [max_contour], 0, (255) ，-1))。尝试在 max_aspect 附近定义 max_contour，也可以通过带有遮罩的线访问。

max_aspect = 0
max_contour = 0

编辑：问题是，仅当且仅当轮廓列表中存在轮廓（变量contours）时才会更新max_contour。因此，max_contour 的默认值不会被 drawContours 接受，因为它期望一个非空轮廓（因此 (-215:Assertion failed) npoints > 0您遇到的错误）。

解决方案是仅在找到轮廓时才创建蒙版。如果没有，我们可以返回原始图像，因为没有可应用的掩模。

所以代码看起来像这样：

max_contour = []  # Let's initialize to a list instead of 0 since I think that would make more sense. This has no effect on the code itself.
max_aspect = 0
for cntr in contours:
    x,y,w,h = cv2.boundingRect(cntr)
    aspect = w/h
    if aspect > max_aspect:
        max_aspect = aspect
        max_contour = cntr

if contours: # This checks if the list of contours is not empty. You could also do `if max_contour:` since that should be satisfied if `max_contour` is non-empty.
    # create mask from max_contour
    mask = np.zeros((ht,wd), dtype=np.uint8)
    ...   # The rest of the code until `return result`
    return result
else:
    return img   # return the original image if the list of contours is empty