- MIoU（Mean IoU，Mean Intersection over Union，均交并比，交集 / 并集），也就是语义分割中所谓的 Mask IoU 。
- MIoU：计算两圆交集（橙色TP）与两圆并集（红色FN 橙色TP 黄色FP）之间的比例，理想情况下两圆重合，比例为1。
代码语言：javascript
复制 from sklearn.metrics import confusion_matrix
import numpy as np
def compute_iou(y_pred, y_true):
# ytrue, ypred is a flatten vector
y_pred = y_pred.flatten()
y_true = y_true.flatten()
current = confusion_matrix(y_true, y_pred, labels=[0, 1])
# compute mean iou
intersection = np.diag(current)
ground_truth_set = current.sum(axis=1)
predicted_set = current.sum(axis=0)
union = ground_truth_set predicted_set - intersection
IoU = intersection / union.astype(np.float32)
return np.mean(IoU)
