I want to apply and examine random forest classification results on landsat 8 image collection in Google Earth Engine (as modified from the origin code in Earth Engine Tutorials)

Accordingly I developed such a code:

var classNames = urban.merge(water).merge(forest);

var roi = ee.Geometry.Point(30.8814, 37.8253);

function scaleFactor(image) {

  // Apply the scaling factors to the appropriate bands.
  var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
  var thermalBands = image.select('ST_B.*').multiply(0.00341802).add(149.0);

  // Replace the original bands with the scaled ones and apply the masks.
  return image.addBands(opticalBands, null, true)
      .addBands(thermalBands, null, true)

// Map the function over one year of data.
var collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
                     .filterDate('2021-01-01', '2021-11-15')
                     .select(['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7','ST_B10'])

// Display the results.
Map.centerObject(roi, 12);  
Map.addLayer(collection.clip(roi), {bands: ['SR_B4', 'SR_B3', 'SR_B2'], min: 0, max: 0.3},'Landsat 8 Imagary');

var landsat = ee.Image(collection);

var training = landsat.addBands(classNames).sample({
  numPixels: 5000,
  seed: 0
var classifier = ee.Classifier.smileRandomForest(10)
      features: training,
      classProperty: 'landcover',
      inputProperties: ['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7','ST_B10']
 var classified = landsat.classify(classifier);

Map.addLayer(landsat, {bands: ['SR_B4', 'SR_B3', 'SR_B2'], max: 0.4}, 'landsat');
Map.addLayer(classified, {}, 'Random Forest Classification');  

but the code stoped by error:

FeatureCollection (Error)
Image.addBands, argument 'srcImg': Invalid type.
Expected type: Image<unknown bands>.
Actual type: FeatureCollection.

i try to convert my feature class to image type but that does not worked any way

Is there any suggesstion for me to solve that?


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