我使用無監(jiān)督維納算法應(yīng)用了圖像反卷積，并增加了特定數(shù)據(jù)集的清晰度和對(duì)比度。但是我在編譯代碼時(shí)遇到了錯(cuò)誤。它顯示AttributeError: 'numpy.ndarray' 對(duì)象沒有屬性 'convert'。如何解決？我的代碼如下 -import cv2import globfrom matplotlib import pyplot as pltfrom skimage import io, color, restoration, img_as_floatimport scipy.stats as stimport numpy as npfrom PIL import Imagefrom PIL import ImageEnhanceall_img = glob.glob('input/*.png')other_dir = 'output/'for img_id, img_path in enumerate(all_img):    img = img_as_float(io.imread(img_path,0))    def gkern(kernlen=21, nsig=2):           lim = kernlen//2 + (kernlen % 2)/2        x = np.linspace(-lim, lim, kernlen+1)        kern1d = np.diff(st.norm.cdf(x))        kern2d = np.outer(kern1d, kern1d)        return kern2d/kern2d.sum()    psf = gkern(5,3)       deconvolved, _ = restoration.unsupervised_wiener(img, pdf)    # Applied Sharpness and contrast    enhancer_object = ImageEnhance.Contrast(deconvolved)    out = enhancer_object.enhance(1.4)    enhancer = ImageEnhance.Sharpness(out)    enhanced_im = enhancer.enhance(8.0)      enhanced_cv_im = np.array(enhanced_im)    cl2 = cv2.resize(enhanced_cv_im, (512,512), interpolation = cv2.INTER_CUBIC)    plt.imsave(f"output/unsupervised_wiener_{img_id}.png", cl2, cmap='gray')它顯示了錯(cuò)誤-runfile('C:/Users/Junaed/.spyder-py3/unsupervised_wiener.py', wdir='C:/Users/Junaed/.spyder-py3')Traceback (most recent call last):  File "C:\Users\Junaed\.spyder-py3\unsupervised_wiener.py", line 37, in <module>    enhancer_object = ImageEnhance.Contrast(deconvolved)AttributeError: 'numpy.ndarray' object has no attribute 'convert'