23 lines
730 B
Python
23 lines
730 B
Python
import numpy as np
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# 假设这是从图像中提取的2个特征图
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feature_map1 = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
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feature_map2 = np.array([[1, 1, 1], [1, 0, 0], [1, 0, 0]])
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# 补全代码：将特征图展平为向量
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vector1 = feature_map1.flatten() # 展平
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vector2 = feature_map2.flatten() # 展平
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print("vector1:", vector1)
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print("vector2:", vector2)
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# 1. 计算欧几里得距离
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euclidean_dist = np.linalg.norm(vector1 - vector2)
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# 2. 计算余弦相似度
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cos_sim = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
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# 输出结果
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print("\n===== 计算结果 =====")
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print("欧几里得距离：", euclidean_dist)
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print("余弦相似度：", cos_sim) |