完成作业

XWL.py

@@ -0,0 +1,17 @@
+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 = np.clip(image - 20, 0, 255)
+print("\n1. 变暗20后:")
+print(image_dark)
+image_crop = image[0:2, 0:2]
+print("\n2. 裁剪左上角(2x2):")
+print(image_crop)
+image_flip = np.fliplr(image)
+print("\n3. 水平翻转:")
+print(image_flip)

XWL2.py

@@ -0,0 +1,17 @@
+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"1. 白色像素(255)数量: {white_count}")
+print(f"   黑色像素(0)数量: {black_count}")
+img_flipped = np.fliplr(img)
+print("\n2. 水平翻转后:")
+print(img_flipped)
+img_rotated = np.fliplr(img.T)
+print("\n3. 逆时针旋转90度后:")
+print(img_rotated)

XWL3.py

@@ -0,0 +1,11 @@
+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(f"\n1. 欧几里得距离: {euclidean_dist:.4f}")
+cos_sim = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
+print(f"2. 余弦相似度: {cos_sim:.4f}")