在 cv2.saliency 上应用 k-means 时出现问题

Question

我正在从事检测人员的项目。所以我在 opencv 中使用显着性并对显着性的输出应用 k-means 聚类。

问题是应用 k-means 聚类后的输出完全是黑色的

代码如下：

import cv2
import time
import numpy as np

cap=cv2.VideoCapture("video.avi")

while(cap.isOpened()):
    #time.sleep(0.05)
    _,frame=cap.read()

    image=frame 

    saliency = cv2.saliency.StaticSaliencySpectralResidual_create()
    (success, saliencyMap) = saliency.computeSaliency(image)
    saliencyMap = (saliencyMap * 255).astype("uint8")

    #cv2.imshow("Image", image)
    #cv2.imshow("Output", saliencyMap)

    saliency = cv2.saliency.StaticSaliencyFineGrained_create()
    (success, saliencyMap) = saliency.computeSaliency(image)
    threshMap = cv2.threshold(saliencyMap.astype("uint8"), 0, 255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

    # show the images
    #cv2.imshow("Image", image)
    cv2.imshow("saliency", saliencyMap)
    #cv2.imshow("Thresh", threshMap)
    
    
    ##############implementing k-means clustering#######################
    kouts=saliencyMap
    clusters=7
    z=kouts.reshape((-1,3))

    z=np.float32(z)

    criteria= (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,10,1.0)

    ret,label,center=cv2.kmeans(z,clusters,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)

    center=np.uint8(center)
    res=center[label.flatten()]
    kouts=res.reshape((kouts.shape))


    cv2.imshow('clustered image',kouts)

    
    k = cv2.waitKey(1) & 0xff
    if k == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

这是我测试算法的视频的link。谁能指出错误或更正？

提前致谢。

Answer 1

关键是在创建地图后将格式转换为 uint8 并将强度缩放 255。您对第一种类型的显着性地图执行了此操作，但没有对第二种类型执行此操作：

saliency = cv2.saliency.StaticSaliencyFineGrained_create()
(success, saliencyMap) = saliency.computeSaliency(image)
### ADDED
saliencyMap = (saliencyMap * 255).astype("uint8")

在 cv2.saliency 上应用 k-means 时出现问题

problem while applying k-means on cv2.saliency

python

opencv

k-means