KMeansClassification otbcli_KMeansClassification Unsupervised KMeans image classification Learning Unsupervised KMeans image classification ParameterRaster in Input Image Input image to classify. False OutputRaster out Output Image Output image containing the class indexes. ParameterNumber ram Available RAM (Mb) Available memory for processing (in MB) 128 True ParameterRaster vm Validity Mask Validity mask. Only non-zero pixels will be used to estimate KMeans modes. True ParameterNumber ts Training set size Size of the training set (in pixels). 100 True ParameterNumber nc Number of classes Number of modes, which will be used to generate class membership. 5 False ParameterNumber maxit Maximum number of iterations Maximum number of iterations for the learning step. 1000 True ParameterNumber ct Convergence threshold Convergence threshold for class centroid (L2 distance, by default 0.0001). 0.0001 True OutputFile outmeans Centroid filename Output text file containing centroid positions