简单介绍NMS的实现方法
https://www.jb51.net/article/229498.htm
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon May 7 21:45:37 2018 @author: lps """ import numpy as np 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 ] 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 :]]) # calculate the points of overlap y11 = np.maximum(y1[i], y1[index[ 1 :]]) x22 = np.minimum(x2[i], x2[index[ 1 :]]) y22 = np.minimum(y2[i], y2[index[ 1 :]]) w = np.maximum( 0 , x22 - x11 + 1 ) # 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 ] 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) 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" ) plot_bbox(boxes, 'k' ) # before nms keep = py_cpu_nms(boxes, thresh = 0.7 ) plot_bbox(boxes[keep], 'r' ) # after nms |
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