# tf.compat.v1.metrics.mean_iou

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/metrics_impl.py#L1282-L1382) |

Calculate per-step mean Intersection-Over-Union (mIOU).

    tf.compat.v1.metrics.mean_iou(
        labels,
        predictions,
        num_classes,
        weights=None,
        metrics_collections=None,
        updates_collections=None,
        name=None
    )

Mean Intersection-Over-Union is a common evaluation metric for
semantic image segmentation, which first computes the IOU for each
semantic class and then computes the average over classes.
IOU is defined as follows:
IOU = true_positive / (true_positive + false_positive + false_negative).
The predictions are accumulated in a confusion matrix, weighted by `weights`,
and mIOU is then calculated from it.

For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean_iou`.

If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.

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| ## Args ||
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| `labels` | A `Tensor` of ground truth labels with shape \[batch size\] and of type `int32` or `int64`. The tensor will be flattened if its rank \> 1. |
| `predictions` | A `Tensor` of prediction results for semantic labels, whose shape is \[batch size\] and type `int32` or `int64`. The tensor will be flattened if its rank \> 1. |
| `num_classes` | The possible number of labels the prediction task can have. This value must be provided, since a confusion matrix of dimension = \[num_classes, num_classes\] will be allocated. |
| `weights` | Optional `Tensor` whose rank is either 0, or the same rank as `labels`, and must be broadcastable to `labels` (i.e., all dimensions must be either `1`, or the same as the corresponding `labels` dimension). |
| `metrics_collections` | An optional list of collections that `mean_iou` should be added to. |
| `updates_collections` | An optional list of collections `update_op` should be added to. |
| `name` | An optional variable_scope name. |

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| ## Returns ||
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| `mean_iou` | A `Tensor` representing the mean intersection-over-union. |
| `update_op` | An operation that increments the confusion matrix. |

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| ## Raises ||
|---|---|
| `ValueError` | If `predictions` and `labels` have mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions`, or if either `metrics_collections` or `updates_collections` are not a list or tuple. |
| `RuntimeError` | If eager execution is enabled. |

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