简介

提供了常用的非监督分类分类器。

em

em(Expectation Maximization)非监督分类分类器。

函数	返回值
em(nClusters)	PIEEM分类器

参数	类型	说明
nClusters	Int	分类的数目

示例

Map = pie.Map()
geometry = pie.Geometry.Polygon([[[116.953, 39.419], [117.078, 39.419], [117.078, 39.477],[116.953,39.477],[116.953, 39.419]]], None)
image = pie.Image("user/101/public/Raster/GF1_Clip").select(["B1","B2","B3"])
training = image.sample(geometry, 20, "", "", 200)
cluster = pie.em(5).train(training).getInfo()
resultImage = image.cluster(cluster,"clusterA")
visParam = {
  'opacity':1,
  'classify':'0,1,2,3,4,5,6',
  'palette': 'FF0000,00FFFF,00FF00,FF00FF,0000FF,FFFF00,FF8000,00AAFF'
}
Map.addLayer(resultImage,visParam,'em_result')
Map.setCenter(117.01,39.45,13)
Map

kMeans

Kmeans非监督分类分类器。

函数	返回值
kMeans(nClusters)	PIEKMeans分类器

参数	类型	说明
nClusters	Int	分类的数目

示例

Map = pie.Map()
geometry = pie.Geometry.Polygon([[[116.953, 39.419], [117.078, 39.419], [117.078, 39.477],[116.953,39.477],[116.953, 39.419]]], None)
image = pie.Image("user/101/public/Raster/GF1_Clip").select(["B1","B2","B3"])
training = image.sample(geometry,20,"","",200)
cluster = pie.kMeans(5).train(training)
resultImage = image.cluster(cluster,"clusterA")
visParam = {
    'opacity':1,
    'classify':'0,1,2,3,4,5,6',
    'palette': 'FF0000,00FFFF,00FF00,FF00FF,0000FF,FFFF00,FF8000,00AAFF'}
Map.addLayer(pieObject=resultImage, style=visParam, name="KMeans")
Map.setCenter(117.01, 39.45, 13)
Map

train

非监督分类分类器训练。

函数	返回值
train(features)	非监督分类器训练结果

参数	类型	说明
features	FeatureCollection	采样点

示例

Map = pie.Map()
geometry = pie.Geometry.Polygon([[[116.953, 39.419], [117.078, 39.419], [117.078, 39.477],[116.953,39.477],[116.953, 39.419]]], None)
image = pie.Image("user/101/public/Raster/GF1_Clip").select(["B1","B2","B3"])
training = image.sample(geometry,20,"","",200)
cluster = pie.kMeans(5).train(training)
resultImage = image.cluster(cluster,"clusterA")
visParam = {
    'opacity':1,
    'classify':'0,1,2,3,4,5,6',
    'palette': 'FF0000,00FFFF,00FF00,FF00FF,0000FF,FFFF00,FF8000,00AAFF'}
Map.addLayer(pieObject=resultImage, style=visParam, name="KMeans")
Map.setCenter(117.01, 39.45, 13)
Map