Clusterer
# 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
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上次更新: 2022/05/25, 07:37:39