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zxy.py

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+import numpy as np
+
+image = np.array([
+    [100, 150, 200],
+    [80, 120, 180],
+    [60, 90, 140]
+], dtype=np.uint8)
+
+print("原图：")
+print(image)
+
+image_dark = (image.astype(np.int16) - 20).clip(0, 255).astype(np.uint8)
+print("\n变暗20后：")
+print(image_dark)
+
+image_crop = image[0:2, 0:2]
+print("\n裁剪左上角后：")
+print(image_crop)
+
+image_flip = np.fliplr(image)
+print("\n水平翻转后：")
+print(image_flip)

zxy1.py

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+import numpy as np
+
+img = np.array([
+    [255, 255, 0,   0],
+    [255, 255, 0,   0],
+    [0,   0,   255, 255],
+    [0,   0,   255, 255]
+], dtype=np.uint8)
+
+white_count = np.sum(img == 255)
+black_count = np.sum(img == 0)
+print(f"白色像素数量：{white_count}")
+print(f"黑色像素数量：{black_count}")
+
+img_flip = np.fliplr(img)
+print("\n水平翻转后的图像：")
+print(img_flip)
+
+img_rot90 = np.fliplr(img.T)
+print("\n逆时针旋转90度后的图像：")
+print(img_rot90)

zxy2.py

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+import numpy as np
+
+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]])
+
+vector1 = feature_map1.flatten()  
+vector2 = feature_map2.flatten() 
+
+print("vector1:", vector1)
+print("vector2:", vector2)
+
+euclidean_dist = np.linalg.norm(vector1 - vector2)
+print("欧几里得距离:", euclidean_dist)
+
+cos_similarity = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
+print("余弦相似度:", cos_similarity)