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image.py
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"""
License:
This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0.
If a copy of the MPL was not distributed with this file, You can obtain one at https://mozilla.org/MPL/2.0/.
"""
from typing import Tuple
import numpy as np
from hub.schema.features import Tensor
class Image(Tensor):
"""| `HubSchema` for images.
Output: `tf.Tensor` of type `tf.uint8` and shape `[height, width, num_channels]`
for BMP, JPEG, and PNG images
Example:
----------
>>> image_tensor = Image(shape=(None, None, 1),
>>> encoding_format='png')
"""
def __init__(
self,
shape: Tuple[int, ...] = (None, None, 3),
dtype="uint8",
# TODO Add back encoding_format (probably named compress) when support for png and jpg support will be added
max_shape: Tuple[int, ...] = None,
chunks=None,
compressor="lz4",
):
"""| Construct the connector.
Parameters
----------
shape: tuple of ints or None
The shape of decoded image:
(height, width, channels) where height and width can be None.
Defaults to (None, None, 3).
dtype: `uint16` or `uint8` (default)
`uint16` can be used only with png encoding_format
encoding_format: 'jpeg' or 'png' (default)
Format to serialize np.ndarray images on disk.
max_shape : Tuple[int]
Maximum shape of tensor shape if tensor is dynamic
chunks : Tuple[int] | True
Describes how to split tensor dimensions into chunks (files) to store them efficiently.
It is anticipated that each file should be ~16MB.
Sample Count is also in the list of tensor's dimensions (first dimension)
If default value is chosen, automatically detects how to split into chunks
Returns
----------
`tf.Tensor` of type `tf.uint8` and shape `[height, width, num_channels]`
for BMP, JPEG, and PNG images
Raises
----------
ValueError: If the shape, dtype or encoding formats are invalid
"""
self._set_dtype(dtype)
super().__init__(
shape,
dtype,
max_shape=max_shape,
chunks=chunks,
compressor=compressor,
)
def _set_dtype(self, dtype):
"""Set the dtype."""
dtype = str(np.dtype(dtype))
if dtype not in ("uint8", "uint16"):
raise ValueError(f"Not supported dtype for {self.__class__.__name__}")
self.dtype = dtype
def __str__(self):
out = super().__str__()
out = "Image" + out[6:]
return out
def __repr__(self):
return self.__str__()