使用 Python 和 OpenCV 进行图像聚类

人工智能等各类编程培训资料整理，所有资源无秘无压缩-购买会员

importnumpyasnp

importcv2

importmatplotlib.pyplotasplt

image=cv2.imread(/input/hillstation/hillstation.jpg)

plt.imshow(image)#originalimage

i=image.sum(axis=2)#converttheshapeofimagein2dimensions

i.shape

(183,275)

img=cv2.cvtColor(image,cv2.COLOR_BGR2RGB)

plt.imshow(img)#converttheimageintoRGB

vector=img.reshape((-1,3))#convertthemXNX3imageintokX3matrixwherek=mXnandeachrowwillbeavectorin3dimensionsspace

vector

array([[55,61,111],

[55,61,111],

[55,61,113],

…,

[42,40,25],

[35,33,18],

[28,26,13]],dtype=uint8)

vector=np.float32(vector)#converttheuint8valuestofloatvalues.k-meansmethodtoopencv

vector

array([[55.,61.,111.],

[55.,61.,111.],

[55.,61.,113.],

…,

[42.,40.,25.],

[35.,33.,18.],

[28.,26.,13.]],dtype=float32)

#clusteringintomultiplelabelsasthepicturehasmultiplecolours.

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

#firstparameterisusedforstopthecriteriaiftheaccuracyisachieved

#secondparameterisusedforstopthealgorithmafterhespecifiednumberofiterations

#cistheiterationterminationprocess.Whentheiterationissatisfied,thealgorithmwillstop.

k=5#numberofclusters

attempts=10#numberoftimesthealgorithmisexecutedusingdifferentlabelings.

ret,label,center=cv2.kmeans(vector,k,None,c,attempts,cv2.KMEANS_PP_CENTERS)

#cv2.kmeans_pp_centersisusedtospecifyhowinitialcentersaretaken

center=np.uint8(center)

res=center[label.flatten()]#accessthelabeltoregeneratetheimage

im=res.reshape(img.shape)

#visualization

x=8

y=6

plt.figure(figsize=(x,y))

plt.subplot(1,2,1)

plt.imshow(img)

plt.title(originalimage)

plt.axis(False)

plt.subplot(1,2,2)

plt.imshow(im)

plt.title(Clusteredimage)

plt.axis(False)

(-0.5,274.5,182.5,-0.5)

原始图像与聚类图像