# Keras IoU implementation

Are there any implementations of **Intersection over Union** metric in Keras 2.1.*?

Are there any implementations of **Intersection over Union** metric in Keras 2.1.*?

1 Answers

NN

3```
def mean_iou(y_true, y_pred):
y_pred = K.cast(K.greater(y_pred, .5), dtype='float32') # .5 is the threshold
inter = K.sum(K.sum(K.squeeze(y_true * y_pred, axis=3), axis=2), axis=1)
union = K.sum(K.sum(K.squeeze(y_true + y_pred, axis=3), axis=2), axis=1) - inter
return K.mean((inter + K.epsilon()) / (union + K.epsilon()))
```

Reply

AS

0Zoe, he knew cause he's smart

NN

0It's not difficult. Remember we are talking about masks and **y_true**, **y_pred are matrices with 0 or 1. The operations are pixelwise**

**Intersection = y_true * y_pred** // all pixel locations, which are 1 for both y_true and y_pred

**Union = y_true + y_pred - Intersection **// combines all pixel locations from y_true and y_pred. If we just add y_true and y_pred we will calculate their common part twice, that's why we subtract their intersection.

the sum function and axis arguments are just parameters and it's a way to understand the shapes of y_true and y_pred.

ZG

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