260416-2509165004

2.py

@@ -0,0 +1,16 @@
+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)
+euclidean_dist = np.linalg.norm(vector1 - vector2)
+print("欧几里得距离：",euclidean_dist)
+cos_sim = np.dot(vector1,vector2)/(np.linalg.norm(vector1)*np.linalg.norm(vector2))
+print("余弦相似度：",cos_sim)

260416-2509165004.py

@@ -0,0 +1,18 @@
+import numpy as np
+
+image = np.array([
+    [100, 150, 200],
+    [80,  120, 180],
+    [60,  90,  140]
+], dtype=np.uint8)
+
+print("原图：")
+print(image)
+print()
+image_crop = image[0:2,0:2]
+print("裁剪左上角2x2后:")
+print(image_crop)
+print()
+image_flip = np.fliplr(image)
+print("水平翻滚后：")
+print(image_flip)