tf.compat.v1.extract_image_patches

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Extract patches from images and put them in the "depth" output dimension.

tf.compat.v1.extract_image_patches(
    images, ksizes=None, strides=None, rates=None, padding=None, name=None,
    sizes=None
)

Args:

• images: A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. 4-D Tensor with shape [batch, in_rows, in_cols, depth].
• ksizes: A list of ints that has length >= 4. The size of the sliding window for each dimension of images.
• strides: A list of ints that has length >= 4. How far the centers of two consecutive patches are in the images. Must be: [1, stride_rows, stride_cols, 1].
• rates: A list of ints that has length >= 4. Must be: [1, rate_rows, rate_cols, 1]. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1), followed by subsampling them spatially by a factor of rates. This is equivalent to rate in dilated (a.k.a. Atrous) convolutions.
• padding: A string from: "SAME", "VALID". The type of padding algorithm to use.
• name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as images.