# tf.keras.applications.inception_resnet_v2.preprocess_input

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.14.0/keras/applications/inception_resnet_v2.py#L421-L425) |

Preprocesses a tensor or Numpy array encoding a batch of images.

    tf.keras.applications.inception_resnet_v2.preprocess_input(
        x, data_format=None
    )

Usage example with [`applications.MobileNet`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/keras/applications/mobilenet/MobileNet):

    i = tf.keras.layers.Input([None, None, 3], dtype = tf.uint8)
    x = tf.cast(i, tf.float32)
    x = tf.keras.applications.mobilenet.preprocess_input(x)
    core = tf.keras.applications.MobileNet()
    x = core(x)
    model = tf.keras.Model(inputs=[i], outputs=[x])

    image = tf.image.decode_png(tf.io.read_file('file.png'))
    result = model(image)

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| ## Args ||
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| `x` | A floating point `numpy.array` or a [`tf.Tensor`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/Tensor), 3D or 4D with 3 color channels, with values in the range \[0, 255\]. The preprocessed data are written over the input data if the data types are compatible. To avoid this behaviour, `numpy.copy(x)` can be used. |
| `data_format` | Optional data format of the image tensor/array. None, means the global setting [`tf.keras.backend.image_data_format()`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/keras/backend/image_data_format) is used (unless you changed it, it uses "channels_last"). Defaults to `None`. |

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| ## Returns ||
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| Preprocessed `numpy.array` or a [`tf.Tensor`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/Tensor) with type `float32`. <br /> The inputs pixel values are scaled between -1 and 1, sample-wise. ||

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| ## Raises ||
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| `ValueError` | In case of unknown `data_format` argument. |

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