import numpy as np

# 假设这是从图像中提取的2个特征图
feature_map1 = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
feature_map2 = np.array([[1, 1, 1], [1, 0, 0], [1, 0, 0]])

# 补全代码：将特征图展平为向量
vector1 = feature_map1.flatten()  # 展平
vector2 = feature_map2.flatten()  # 展平

print("vector1:", vector1)
print("vector2:", vector2)
print("-" * 40)

# 1. 计算欧几里得距离
euclidean_dist = np.linalg.norm(vector1 - vector2)
print("欧几里得距离：", euclidean_dist)

# 2. 计算余弦相似度
cos_sim = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
print("余弦相似度：", cos_sim)