云视觉模型图像找不到相似性

import numpy as np
from tensorflow.keras.applications.vgg16 import VGG16, preprocess_input
from tensorflow.keras.preprocessing import image
from sklearn.metrics.pairwise import cosine_similarity

# 加载预训练的VGG16模型
model = VGG16(weights='imagenet', include_top=False)

# 加载目标图像和待比较图像
target_img_path = 'path_to_target_image.jpg'
compare_img_path = 'path_to_compare_image.jpg'

# 预处理图像
target_img = image.load_img(target_img_path, target_size=(224, 224))
compare_img = image.load_img(compare_img_path, target_size=(224, 224))

target_img_data = image.img_to_array(target_img)
compare_img_data = image.img_to_array(compare_img)

target_img_data = np.expand_dims(target_img_data, axis=0)
compare_img_data = np.expand_dims(compare_img_data, axis=0)

target_img_data = preprocess_input(target_img_data)
compare_img_data = preprocess_input(compare_img_data)

# 提取图像特征
target_features = model.predict(target_img_data)
compare_features = model.predict(compare_img_data)

# 计算相似性
similarity = cosine_similarity(target_features.reshape(1, -1), compare_features.reshape(1, -1))

print(f'Similarity: {similarity[0][0]}')