我正在尝试为测试视频生成预测，但出现此错误（IndexError：用作索引的数组必须是整数（或布尔）类型）

Question

这是我为模型中的测试视频生成预测的代码，它是这样工作的

首先，我们将创建两个空列表——一个用于存储预测，另一个用于存储实际标签 然后，我们将从测试集中取出每个视频，提取该视频的帧并将其存储在一个文件夹中（在当前目录中创建一个名为 temp 的文件夹来存储帧）。我们将在每次迭代时从此文件夹中删除所有其他文件 接下来，我们将从临时文件夹中读取所有帧，使用预训练模型提取这些帧的特征，预测标签，然后采用模式为该特定视频分配标签并将其附加到列表中 我们将为第二个列表中的每个视频附加实际标签

# creating two lists to store predicted and actual tags
predict = []
actual = []

# for loop to extract frames from each test video
count = 0
for i in tqdm(range(test_videos.shape[0])):
    videoFile = test_videos[i]
    cap = cv2.VideoCapture(test_videos[i])   # capturing the video from the given path
    frameRate = cap.get(cv2.CAP_PROP_FPS) #frame rate
    x=1
    # removing all other files from the temp folder
    files = glob('E:/FCI Bio/GP/Dataset/Paper/3/3.1/OHP/Labeled_Dataset/videos/dataset/test/temp/*')
    for f in files:
        os.remove(f)
    while(cap.isOpened()):
        frameId = cap.get(1) #current frame number
        ret, frame = cap.read()
        if (ret != True):
            break
        if (frameId % math.floor(frameRate) == 0):
            # storing the frames of this particular video in temp folder
            filename ='E:/FCI Bio/GP/Dataset/Paper/3/3.1/OHP/Labeled_Dataset/videos/dataset/test/temp/' + os.path.basename(videoFile).split('_')[0] + "_frame%d.jpg" % count;count+=1
            cv2.imwrite(filename, frame)
    cap.release()
    
    # reading all the frames from temp folder
    images = glob("E:/FCI Bio/GP/Dataset/Paper/3/3.1/OHP/Labeled_Dataset/videos/dataset/test/temp/*.jpg")
    
    prediction_images = []
    for i in range(len(images)):
        img = image.load_img(images[i], target_size=(224,224,3))
        img = image.img_to_array(img)
        img = img/255
        prediction_images.append(img)
        
    # converting all the frames for a test video into numpy array
    prediction_images = np.array(prediction_images)
    # extracting features using pre-trained model
    prediction_images = base_model.predict(prediction_images)
    # converting features in one dimensional array
    prediction_images = prediction_images.reshape(prediction_images.shape[0], 7*7*512)
    # predicting tags for each array
    prediction = model.predict(prediction_images)
    # appending the mode of predictions in predict list to assign the 
    tag to the video
    predict.append(y.columns.values[s.mode(prediction)[0][0]])
    # appending the actual tag of the video
    actual.append(os.path.basename(videoFile).split('_')[0])

这是错误

IndexError                                Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_4364\3325358529.py in <module>
     44     prediction = model.predict(prediction_images)
     45     # appending the mode of predictions in predict list to assign the tag to the video
---> 46     predict.append(y.columns.values[s.mode(prediction)[0][0]])
     47     # appending the actual tag of the video
     48     actual.append(os.path.basename(videoFile).split('_')[0])

IndexError: arrays used as indices must be of integer (or boolean) type