我不断尝试，我认为列表项在列表的范围内，但显然不是？真的不知道我做错了什么。错误在第57行或

prediction_text = f"{classes[class_index]}: {confidence:.2f}%"

代码：

import tensorflow as tf
import numpy as np
import cv2
import os

print(tf.__version__)
print(cv2.__version__)

#paths for image and models, will work on later for live image recog
image_path = 'object recog/images/1.png'
prototxt_path = 'A:\MobileNetSSD_deploy.prototxt'
model_path = 'A:\MobileNetSSD_deploy.caffemodel'
min_confidence = 0.2

#what objects to recog
classes = ['BG', 'person']
#filler BG as in list needs index at 0 for background appropriately named BG, then classes are defined....

#box colors, when surrounding element
colors = np.random.seed(42)

#load pre-trained model
net = cv2.dnn.readNet(prototxt_path, model_path)

#image elements
image = cv2.imread(image_path)
height, width = image.shape[0], image.shape[1]

#BLOB, store image as binary code, scale factor : 2nd number after 300, ratio for scaling between old and new image
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 0.007, (300, 300), 130)

#prediction
net.setInput(blob)
detected_objects = net.forward()

print(detected_objects[0][0][1])
#output example [ 0.         15.          0.7585785   0.63882416  0.2551059   0.75395054 0.6825095 ]
#2nd number is class index, 3rd is confidence, rest is coordinates from upper left upper right lower left lower right respectively
#max 6 right now

font_text = cv2.FONT_HERSHEY_SIMPLEX

for i in range(detected_objects.shape[1]):
    confidence = detected_objects[0][0][i][2]
    if confidence > min_confidence:
        class_index = int(detected_objects[0, 0, i, 1])

        upper_left_x = int(detected_objects[0][0][i][3] * width)
        upper_left_y = int(detected_objects[0][0][i][4] * width)
        lower_right_x = int(detected_objects[0][0][i][5] * width)
        lower_right_y = int(detected_objects[0][0][i][6] * width)

        text_y_coords = upper_left_y - 15 if upper_left_y < 30 else upper_left_y + 15
        #decides if coordinate of class text is going to be above or below the rectangle depending on if the coords of rectangle are close to top line

        #f string for niceness
        prediction_text = f"{classes[class_index]}: {confidence:.2f}%"
        cv2.rectangle(image, (upper_left_x, upper_left_y), (lower_right_x, lower_right_y), colors[class_index], 2)
        #params: starting point x and y from upper left and ending point x and y from lower right, the randomized colors established, thickness of line
        cv2.putText(image, prediction_text, (upper_left_x, text_y_coords), font_text, 1, colors[class_index], 2)
        #params: image, text, coords where text will be, font, font scale, color, thickness

cv2.imshow("Detected Objects ", image)
cv2.waitKey(0)
#waitkey 0 so doesn't close until a key is pressed
cv2.destroyAllWindows()

尝试更改列表大小，我从另一个堆栈帖子添加了"BG"？？？没有工作困惑