import numpy as np
import matplotlib.pyplot as plt
def py_cpu_nms(nms_show, dets, thresh):# nms 操作
"Pure Python NMS baseline"
# x1 、 y1 、 x2 、 y2 以及 score 赋值
x1 = dets[:,0]
y1 = dets[:,1]
x2 = dets[:,2]
y2 = dets[:,3]
scores = dets[:, 4]
areas = (y2-y1+1) * (x2-x1+1) # 每一个检测框的面积
print("all_areas:",areas)
order = scores.argsort()[::-1]# 按照 score 置信度降序排序
print("order:",order)
keep = [] # 保留的结果框集合
k=0
show_boxid = order
print("show_boxid",show_boxid)
while order.size > 0:
i = order[0] # every time the first is the biggst, and add it directly
keep.append(i) # 保留该类剩余 box 中得分最高的一个
print("\nkeep( 被留下来的框 id):",keep)
# 得到相交区域 , 比左上大和比右下小
'''np.maximum(X, Y, out=None) X 和 Y 逐位进行比较 , 选择最大值 '''
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
print("xx1,yy1:",xx1,yy1)
print("xx2,yy2:",xx2,yy2)
print("w,h:",xx2-xx1+1,yy2-yy1+1)
#plt.scatter([xx1,xx2], [yy1,yy2], s=50, c='y')# 框左上角蓝色
# 计算相交的面积 ,外汇跟单gendan5.com 不重叠时面积为 0
w = np.maximum(0, xx2-xx1+1) # the weights of overlap
h = np.maximum(0, yy2-yy1+1) # the height of overlap
inter = w*h
print("w*h:",inter)
# 计算 IoU ：重叠面积 / （面积 1+ 面积 2- 重叠面积）
iou = inter / (areas[i]+areas[order[1:]] - inter)
print("---iou:",iou)
# 保留 IoU 小于阈值的 box
''' 去掉 keep 剩下的框按顺序重新排序 '''
indx = np.where(iou<=thresh)[0]
dedx = np.where(iou>thresh)[0]
print("order[0]:",order[0])
show_boxid = np.delete(show_boxid,np.where(show_boxid==order[0])[0],axis = 0)
print("show_boxid:",np.append(keep,show_boxid))
delete_boxid = show_boxid[dedx]
show_boxid = show_boxid[indx]
#print("indx:",indx)
print("after_iou_show_boxid:",np.append(keep,show_boxid))
print("after_iou_delete_boxid:",delete_boxid,'\n')
k=k+1
''' 绘制动图 '''
ax1 = nms_show.add_subplot(1,2,1)
ax1.set_title('begin_nms {} \nkeep:{} score:{}({})'.format(k,order[0],scores[order[0]],k))
plot_bbox(dets, 'k', show_ids=np.arange(9) , keep_id = order[0])
ax2 = nms_show.add_subplot(1,2,2)
ax2.set_title('after_nms {} \nkeep:{} delete:{}(iou={})'.format(k,order[0],delete_boxid,iou[dedx]))
plot_bbox(dets[np.append(show_boxid,keep)], 'b', np.append(show_boxid,keep))
plt.pause(5)
ax1.remove()
ax2.remove()
''' 置信度排前的数值给取出，剩下的数构成新的数组 '''
order = order[indx+1]
print("-----------afer_order:",order,'-----------')
return keep
def plot_bbox(dets, c='k', show_ids=[],keep_id=0):
x1 = dets[:,0]
y1 = dets[:,1]
x2 = dets[:,2]
y2 = dets[:,3]
score=dets[:,4]
#print(dets.shape)
#plt.scatter(x1, y1, s=25, c='b', alpha=0.6)# 框左上角蓝色
#plt.scatter(x2, y2, s=25, c='r', alpha=0.6)# 框右下角红色
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.xlim((60,450))
plt.ylim((450,60))
''' 改变坐标轴位置 '''
ax = plt.gca()
ax.spines["top"].set_color("k")
ax.xaxis.set_ticks_position("top")
for i in range(len(show_ids)):
plt.text(x1[i], y1[i]+7, "(%d)%.2f"%(show_ids[i],score[i]), \
fontdict={'size': 10, 'color': 'r'},bbox={'facecolor':'blue', 'alpha':0.1})
if keep_id != 0:
ax.add_patch(plt.Rectangle((x1[keep_id], y1[keep_id]), x2[keep_id]-x1[keep_id]+1, y2[keep_id]-y1[keep_id]+1,
color="y", fill=True, linewidth=2))
def main():
boxes=np.array([
[100,100,210,210,0.72],#0
[280,290,420,420,0.8],#1
[220,220,320,330,0.92],#2
[105,90,220,210,0.71],#3
[230,240,325,330,0.81],#4
[305,300,420,420,0.9],#5
[215,225,305,328,0.6],#6
[150,260,290,400,0.99],#7
[102,108,208,208,0.72]])#8 #9 个框
plt.ion()
fig = plt.figure(figsize=[14,9])
ax1 = plt.subplot(1,2,1)
ax1.set_title('before_nms')
ax2 = plt.subplot(1,2,2)
ax2.set_title('after_nms')
plt.sca(ax1)# 选择子图 1
plot_bbox(boxes,'k',show_ids=np.arange(9),keep_id=0) # before nms
keep = py_cpu_nms(fig, boxes, thresh=0.7)
print("last_keep:",keep)
plt.ioff()
plt.pause(2)
plt.close('all')
if __name__ =="__main__":
main()