K means loop doesn't work for the image clustering

I am using the code in Study 2A in this link (https://github.com/yilangpeng/image-clustering/tree/main/study2A). In the D kmeans clustering, I met some problems because I need assign every label from k means to every picture, but the number of label is 9, the picture is 200, they are not matching well. The following is my code and error information.

import joblib, osimport numpy as npimport pandas as pdfrom sklearn.cluster import KMeansimport ypoften as ofcwd = os.path.join('/content/drive/MyDrive/study2A/for lab teaching',"")# please change this to the folder that has all the imagescvmodels = ["vgg16 fc1"]## cvmodels = ["vgg16 fc1","vgg16 places fc1","vggface fc6"] choose the model you usedclmethod = "KMeans"for cvmodel in cvmodels:    features_savepath = os.path.join(cwd,'img exfeature1','features PCA',cvmodel+'.dat')    features_array = joblib.load(features_savepath)    X = pd.DataFrame(features_array)    print(X)    nd = 200    X = X.iloc[:,0:nd]    savefolder = cvmodel +''+ clmethod +' PCA'+ str(nd)    # Read the 0321_imageselected_A.txt file    imgnamefile = os.path.join(cwd, "0321_imageselected_A.txt")    df = pd.read_csv(imgnamefile, sep='\t', header=0)    for K in [2]:        print('number of cluster', K)        cl = KMeans(K, random_state=0)        cl.fit(X)        labels = cl.labels_        imgnamefile = os.path.join(cwd,"0321_imageselected_A.txt")        df = pd.read_csv(imgnamefile, sep ='\t', header = 0)        print(df)        df['label'] = labels        filepath = os.path.join(cwd,'img cluster',savefolder,str(K),'label.txt')        of.create_path(filepath)        df.to_csv(filepath, index = None, header = None, sep = '\t')    print("DONE"*20)

ValueError: Length of values (9) does not match length of index (200)

I want to have a txt file that includes label so that I can proceed following steps.