[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["缺少我需要的資訊","missingTheInformationINeed","thumb-down"],["過於複雜/步驟過多","tooComplicatedTooManySteps","thumb-down"],["過時","outOfDate","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["示例/程式碼問題","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-07-26 (世界標準時間)。"],[],["K-Means clustering is applied to an input image, generating a single-band output image where each pixel is assigned a cluster ID. Clustering can occur within a fixed grid (`gridSize`) or within overlapping tiles (`neighborhoodSize`). By default, tiles have no overlap. Clusters are independent per cell/tile, potentially resulting in different labels for clusters crossing boundaries. Parameters include the number of clusters and iterations. Convergence can be enforced and the ID labels be unique or repeat depending on the specified parameter.\n"]]