非極大值抑制（NMS）的幾種實(shí)現(xiàn)
非極大值抑制（Non-Maximum Suppression行剂，NMS） : python 代碼實(shí)現(xiàn)和詳細(xì)講解
用matplotlib.pyplot 畫 bounding box:
http://www.reibang.com/p/8d14238d402a
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 7 21:45:37 2018
@author: lps
"""
import numpy as np
import os
os.environ["DISPLAY"] = 'localhost:11.0'
boxes=np.array([[100,100,210,210,0.72],
[250,250,420,420,0.8],
[220,220,320,330,0.92],
[100,100,210,210,0.72],
[230,240,325,330,0.81],
[220,230,315,340,0.9]])
def py_cpu_nms(dets, thresh):
# dets:(m,5) thresh:scaler
x1 = dets[:,0]
y1 = dets[:,1]
x2 = dets[:,2]
y2 = dets[:,3]
areas = (y2-y1+1) * (x2-x1+1)
scores = dets[:,4]
keep = []
index = scores.argsort()[::-1] # 這里面存儲(chǔ)著 分?jǐn)?shù)按照降序排列的 所有框的 索引
while index.size >0:
i = index[0] # every time the first is the biggst, and add it directly
keep.append(i)
x11 = np.maximum(x1[i], x1[index[1:]]) # 左上找盡量右下 # calculate the points of overlap
y11 = np.maximum(y1[i], y1[index[1:]])
x22 = np.minimum(x2[i], x2[index[1:]]) # 右下找盡量左上
y22 = np.minimum(y2[i], y2[index[1:]])
# 以[x11, y11, x22,y22] 構(gòu)成的矩形是與 最高分?jǐn)?shù)相交的矩形
w = np.maximum(0, x22-x11+1) # 這里可能是負(fù)的（兩個(gè)矩形不相交）僧著，負(fù)的這里取寬度為0 # the weights of overlap
h = np.maximum(0, y22-y11+1) # the height of overlap
overlaps = w*h
ious = overlaps / (areas[i]+areas[index[1:]] - overlaps)
idx = np.where(ious<=thresh)[0] # 如果他們的iou小于閾值，說明他們重合的很少，重合的很少的這些框是框的其他目標(biāo)。
# 選出重合較少的框（也就是去掉了框中同一個(gè)目標(biāo)，但是分?jǐn)?shù)比較低的框）。
# 從剩下的里面選擇第0位置面殖，也就是剩下的里面選擇評(píng)分最高的框，進(jìn)行下次 去iou大的框操作哭廉。
index = index[idx+1] # because index start from 1
return keep
import matplotlib.pyplot as plt
def plot_bbox(dets, c='k'):
x1 = dets[:,0]
y1 = dets[:,1]
x2 = dets[:,2]
y2 = dets[:,3]
plt.plot([x1,x2], [y1,y1], c) # plot([起點(diǎn)橫坐標(biāo)脊僚，終點(diǎn)橫坐標(biāo)]，[起點(diǎn)縱左邊遵绰， 終點(diǎn)縱坐標(biāo)])
plt.plot([x1,x1], [y1,y2], c)
plt.plot([x1,x2], [y2,y2], c)
plt.plot([x2,x2], [y1,y2], c)
plt.title("after nms")
plt.subplot(121)
plot_bbox(boxes,'k') # before nms
plt.subplot(122)
keep = py_cpu_nms(boxes, thresh=0.7)
plot_bbox(boxes[keep], 'r')# after nms
plt.show()
