3 高效 NMS

字数 23阅读 30

2 非极大值抑制(NMS)

我们先载入图片:

import numpy as np
from copy import  deepcopy
from matplotlib import pyplot as plt
np.set_printoptions(2)     # 修改了 NumPy 的打印精度
# 指定默认字体, 为在 Matplotlib 中显示中文,设置特殊字体
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号 '-' 显示为方块的问题

%matplotlib inline

img_name = '../images/catdog.jpg'
img = plt.imread(img_name)

1D NMS

代码如下

class NMS:
    '''
    参考论文:Neubeck A, Van Gool L. Efficient Non-Maximum Suppression

    非极大值抑制
    '''

    def __init__(self, I):
        '''
        参数
        ===========
        I::1D 或者 2D 数组
        '''
        self.I = I
        self.__pmax = deepcopy(self.I)

    def __CompPartialMax(self, from_, to):
        '''
        Compute Partial Maximum

        返回
        =========
        max{self.I[from_:to+1]}
        '''
        best = to
        # 从右往左搜索
        while to > from_:
            to -= 1
            if self.I[to] <= self.I[best]:
                self.__pmax[to] = self.I[best]
            else:
                self.__pmax[to] = self.I[to]
                best = to
        return best

    def BlockWise(self, r):
        '''
        r 近邻,即 (2r+1)-Neighborhood
        '''
        w = len(self.I)
        assert 3 * r < w, "邻域半径超出范围"
        i = r
        self.__CompPartialMax(0, i - 1)
        chkpt = -1
        maximuns = []

        while i + 2 * r < w:
            j = self.__CompPartialMax(i, i + r)
            k = self.__CompPartialMax(i + r + 1, j + r)
            if i == j or self.I[j] > self.I[k]:  # self.I[j] 是极大值
                if (chkpt < j - r or self.I[j] >= self.__pmax[chkpt]) and (
                        j - r == i or self.I[j] >= self.__pmax[j - r]):
                    maximuns.append(j)
                if i < j:
                    chkpt = i + r + 1
                i = j + r + 1
            else:
                i = k
                chkpt = j + r + 1
                while i < w - r:
                    j = self.__CompPartialMax(chkpt, i + r)
                    if self.I[i] > self.I[j]:  # # self.I[i] 是极大值
                        maximuns.append(i)
                        i = i + r - 1
                        break
                    else:
                        chkpt = i + r - 1
                        i = j
        return maximuns

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