使用numpy进行非最大值抑制的2D峰值查找

import numpy as np

# 加载图像数据
image = np.load('image.npy')

# 找到图像中的最大值位置
max_positions = np.argwhere(image == np.max(image))

# 定义一个空列表，用于存储非最大值抑制后的峰值位置
peaks = []

# 对每个最大值位置进行非最大值抑制
for position in max_positions:
    x, y = position[0], position[1]
    
    # 判断当前位置是否为局部最大值
    if image[x, y] >= image[x-1, y-1] and image[x, y] >= image[x-1, y] and image[x, y] >= image[x-1, y+1] and \
       image[x, y] >= image[x, y-1] and image[x, y] >= image[x, y+1] and \
       image[x, y] >= image[x+1, y-1] and image[x, y] >= image[x+1, y] and image[x, y] >= image[x+1, y+1]:
        peaks.append(position)

# 计算峰值的坐标和强度
peak_coordinates = [(x, y) for x, y in peaks]
peak_intensities = [image[x, y] for x, y in peaks]