# cv2.error: OpenCV(4.9.0) /modules/core/src/kmeans.cpp:245: 错误: (-215:断言失败) N >= K 在函数 'cv::kmeans' 中

- **ID:** `opencv/kmeans-invalid-clusters`
- **领域:** opencv
- **类别:** assertion_error
- **错误码:** `-215`
- **验证级别:** ai_generated
- **修复率:** 90%

## 根因

数据点数量（N）少于请求的聚类数量（K），导致聚类无法进行。

## 版本兼容性

| 版本 | 状态 | 引入 | 弃用 |
|------|------|------|------|
| 4.5.0 | active | — | — |
| 4.6.0 | active | — | — |
| 4.7.0 | active | — | — |
| 4.8.0 | active | — | — |
| 4.9.0 | active | — | — |

## 解决方案

1. ```
   Reduce the number of clusters K to be at most the number of data points N. Check N before calling kmeans and clamp K accordingly.
   ```
2. ```
   Add more data points by collecting additional samples or using data augmentation to increase N above K.
   ```

## 无效尝试

- **Increase the number of data points by duplicating existing points** — Duplicating points does not add new information and can bias the clustering; the real fix is to reduce K or use more distinct data. (70% 失败率)
- **Use a different clustering algorithm like DBSCAN** — While this avoids the error, it changes the algorithm behavior and may not be appropriate for the use case. (40% 失败率)
- **Set K to a very large number** — Making K larger only exacerbates the N >= K violation. (95% 失败率)