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我正在尝试从 Sentinel SR 图像执行有监督的土地覆盖分类并得到以下错误：

SR_2018.select(...).sampleRegions 不是函数

//import shapefile of study area
var boundary =ee.FeatureCollection(boundary);
Map.setCenter(43.4,5.5, 10)


/**
 * Function to mask clouds using the Sentinel-2 QA band
 * @param {ee.Image} image Sentinel-2 image
 * @return {ee.Image} cloud masked Sentinel-2 image
 */
function maskS2clouds(image) {
  var qa = image.select('QA60');

  // Bits 10 and 11 are clouds and cirrus, respectively.
  var cloudBitMask = 1 << 10;
  var cirrusBitMask = 1 << 11;

  // Both flags should be set to zero, indicating clear conditions.
  var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
      .and(qa.bitwiseAnd(cirrusBitMask).eq(0));
  return image.updateMask(mask).divide(10000);
}

//add an NDVI (Normalized Difference Vegetation Index) band to the images
var NDVI = function(image) {
  // Add an NDVI band
  return image.addBands(image.normalizedDifference(['B8', 'B4']).rename('NDVI'))
};

var dataset_SR = ee.ImageCollection('COPERNICUS/S2_SR')
                  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
                  .filterBounds(ee.FeatureCollection(boundary))
                  .map(function(image){return image.clip(boundary)})
                  .map(NDVI);
print(dataset_SR)


//create yearly median composites by using the available Sentinel SR data
//year 2018
var SR_2018 = dataset_SR
    .filterDate('2018-12-01', '2018-12-31')
    .map(maskS2clouds)
    .map(NDVI);

var SR_2018_median = SR_2018
    .reduce(ee.Reducer.median());

print(SR_2018_median)


//load the training data for the supervised classification
var trainingSites= urban.merge(water).merge(veg_high).merge(soil).merge(veg_med);

//Choose all the median bands available including the median NDVI band. 
//Use only these bands for the prediction
var SR_bands = ['B2_median', 'B3_median', 'B4_median', 'B5_median', 'B6_median','B7_median','B8_median', 'B8A_median', 'B11_median', 'B12_median',                 
                'TCI_R_median', 'TCI_G_median', 'TCI_B_median',
                'NDVI_median'];

//print(image.getInfo()); 
                
// Get the values for all pixels in each polygon in the training.
var trainingData = SR_2018.select(SR_bands).sampleRegions({
  collection: trainingSites,    // Get the sample from the polygons FeatureCollection.
  properties: ['landcover'],    //Keep this list of properties from the polygons.
  scale: 10                    
});


// Get a randomForest classifier and train it- with the training data.
var classifier_Train = ee.Classifier.randomForest(10).train({
    features: trainingData, 
    classProperty: 'landcover', 
    inputProperties: SR_bands //bands
});

我尝试按照这篇文章 https://stackoverflow.com/questions/63984413/image-selectbands-sampleregions-is-not-a-function-error-what-must-i-do 中的建议使用 .toBands() 但确实如此不解决问题。

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