【发布时间】:2018-08-05 02:39:56
【问题描述】:
这是我训练自己的分类器的 HaarCascade 实现。
import cv2
import numpy as np
body_classifier = cv2.CascadeClassifier('C:\\Users\\Nemi\\MasteringComputerVision_V1.00\\Haarcascades\\trainedHuman.xml')
image = cv2.imread("twn2.jpg")
#####HEREEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
bodies,rejectLevels, levelWeights = body_classifier.detectMultiScale3(
image,
scaleFactor=1.1,
minNeighbors=20,
minSize=(24, 24),
maxSize=(96,96),
flags = cv2.CASCADE_SCALE_IMAGE,
outputRejectLevels = True
)
print(rejectLevels)
print(levelWeights)
i = 0
font = cv2.FONT_ITALIC
for (x,y,w,h) in bodies:
cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,255),2)
font = cv2.FONT_HERSHEY_SIMPLEX
#cv2.putText(image,str(i)+str(":")+str(np.log(levelWeights[i][0])),(x,y), font,0.5,(255,255,255),2,cv2.LINE_AA)
cv2.putText(image,str(levelWeights[i][0]),(x,y), font,0.5,(255,255,255),2,cv2.LINE_AA)
i = i+1
cv2.imshow("Detection",image)
cv2.waitKey(0)
cv2.destroyAllWindows()
我想知道这个 levelWeights 是什么意思,为什么值这么小?如果这个levelWeights可以以检测窗口置信度的形式使用我该怎么办?
【问题讨论】:
标签: c++ python-3.x opencv object-detection haar-classifier