# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write images using Pillow/PIL.
Backend Library: `Pillow `_
Plugin that wraps the the Pillow library. Pillow is a friendly fork of PIL
(Python Image Library) and supports reading and writing of common formats (jpg,
png, gif, tiff, ...). For, the complete list of features and supported formats
please refer to pillows official docs (see the Backend Library link).
Parameters
----------
request : Request
A request object representing the resource to be operated on.
Methods
-------
.. autosummary::
:toctree: _plugins/pillow
PillowPlugin.read
PillowPlugin.write
PillowPlugin.iter
PillowPlugin.get_meta
"""
from io import BytesIO
from typing import Callable, Optional, Dict, Any, Tuple, cast, Iterator, Union, List
import numpy as np
from PIL import Image, UnidentifiedImageError, ImageSequence, ExifTags # type: ignore
from ..core.request import Request, IOMode, InitializationError, URI_BYTES
from ..core.v3_plugin_api import PluginV3, ImageProperties
import warnings
from ..typing import ArrayLike
def _exif_orientation_transform(orientation: int, mode: str) -> Callable:
# get transformation that transforms an image from a
# given EXIF orientation into the standard orientation
# -1 if the mode has color channel, 0 otherwise
axis = -2 if Image.getmodebands(mode) > 1 else -1
EXIF_ORIENTATION = {
1: lambda x: x,
2: lambda x: np.flip(x, axis=axis),
3: lambda x: np.rot90(x, k=2),
4: lambda x: np.flip(x, axis=axis - 1),
5: lambda x: np.flip(np.rot90(x, k=3), axis=axis),
6: lambda x: np.rot90(x, k=1),
7: lambda x: np.flip(np.rot90(x, k=1), axis=axis),
8: lambda x: np.rot90(x, k=3),
}
return EXIF_ORIENTATION[orientation]
class PillowPlugin(PluginV3):
def __init__(self, request: Request) -> None:
"""Instantiate a new Pillow Plugin Object
Parameters
----------
request : {Request}
A request object representing the resource to be operated on.
"""
super().__init__(request)
self._image: Image = None
if request.mode.io_mode == IOMode.read:
try:
with Image.open(request.get_file()):
# Check if it is generally possible to read the image.
# This will not read any data and merely try to find a
# compatible pillow plugin (ref: the pillow docs).
pass
except UnidentifiedImageError:
if request._uri_type == URI_BYTES:
raise InitializationError(
"Pillow can not read the provided bytes."
) from None
else:
raise InitializationError(
f"Pillow can not read {request.raw_uri}."
) from None
self._image = Image.open(self._request.get_file())
else:
extension = self.request.extension or self.request.format_hint
if extension is None:
warnings.warn(
"Can't determine file format to write as. You _must_"
" set `format` during write or the call will fail. Use "
"`extension` to supress this warning. ",
UserWarning,
)
return
tirage = [Image.preinit, Image.init]
for format_loader in tirage:
format_loader()
if extension in Image.registered_extensions().keys():
return
raise InitializationError(
f"Pillow can not write `{extension}` files."
) from None
def close(self) -> None:
if self._image:
self._image.close()
self._request.finish()
def read(
self, *, index=None, mode=None, rotate=False, apply_gamma=False
) -> np.ndarray:
"""
Parses the given URI and creates a ndarray from it.
Parameters
----------
index : {integer}
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return it.
If index is an ellipsis (...), read all ndimages in the file and
stack them along a new batch dimension and return them. If index is
None, this plugin reads the first image of the file (index=0) unless
the image is a GIF or APNG, in which case all images are read
(index=...).
mode : {str, None}
Convert the image to the given mode before returning it. If None,
the mode will be left unchanged. Possible modes can be found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
rotate : {bool}
If set to ``True`` and the image contains an EXIF orientation tag,
apply the orientation before returning the ndimage.
apply_gamma : {bool}
If ``True`` and the image contains metadata about gamma, apply gamma
correction to the image.
Returns
-------
ndimage : ndarray
A numpy array containing the loaded image data
Notes
-----
If you open a GIF - or any other format using color pallets - you may
wish to manually set the `mode` parameter. Otherwise, the numbers in
the returned image will refer to the entries in the color pallet, which
is discarded during conversion to ndarray.
"""
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if isinstance(index, int):
# will raise IO error if index >= number of frames in image
self._image.seek(index)
image = self._apply_transforms(self._image, mode, rotate, apply_gamma)
return image
else:
iterator = self.iter(mode=mode, rotate=rotate, apply_gamma=apply_gamma)
image = np.stack([im for im in iterator], axis=0)
return image
def iter(
self, *, mode: str = None, rotate: bool = False, apply_gamma: bool = False
) -> Iterator[np.ndarray]:
"""
Iterate over all ndimages/frames in the URI
Parameters
----------
mode : {str, None}
Convert the image to the given mode before returning it. If None,
the mode will be left unchanged. Possible modes can be found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
rotate : {bool}
If set to ``True`` and the image contains an EXIF orientation tag,
apply the orientation before returning the ndimage.
apply_gamma : {bool}
If ``True`` and the image contains metadata about gamma, apply gamma
correction to the image.
"""
for im in ImageSequence.Iterator(self._image):
yield self._apply_transforms(im, mode, rotate, apply_gamma)
def _apply_transforms(self, image, mode, rotate, apply_gamma) -> np.ndarray:
if mode is not None:
image = image.convert(mode)
elif image.format == "GIF":
# adjust for pillow9 changes
# see: https://github.com/python-pillow/Pillow/issues/5929
image = image.convert(image.palette.mode)
image = np.asarray(image)
meta = self.metadata(index=self._image.tell(), exclude_applied=False)
if rotate and "Orientation" in meta:
transformation = _exif_orientation_transform(
meta["Orientation"], self._image.mode
)
image = transformation(image)
if apply_gamma and "gamma" in meta:
gamma = float(meta["gamma"])
scale = float(65536 if image.dtype == np.uint16 else 255)
gain = 1.0
image = ((image / scale) ** gamma) * scale * gain + 0.4999
image = np.round(image).astype(np.uint8)
return image
def write(
self,
ndimage: Union[ArrayLike, List[ArrayLike]],
*,
mode: str = None,
format: str = None,
is_batch: bool = None,
**kwargs,
) -> Optional[bytes]:
"""
Write an ndimage to the URI specified in path.
If the URI points to a file on the current host and the file does not
yet exist it will be created. If the file exists already, it will be
appended if possible; otherwise, it will be replaced.
If necessary, the image is broken down along the leading dimension to
fit into individual frames of the chosen format. If the format doesn't
support multiple frames, and IOError is raised.
Parameters
----------
image : ndarray or list
The ndimage to write. If a list is given each element is expected to
be an ndimage.
mode : str
Specify the image's color format. If None (default), the mode is
inferred from the array's shape and dtype. Possible modes can be
found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
format : str
Optional format override. If omitted, the format to use is
determined from the filename extension. If a file object was used
instead of a filename, this parameter must always be used.
is_batch : bool
Explicitly tell the writer that ``image`` is a batch of images
(True) or not (False). If None, the writer will guess this from the
provided ``mode`` or ``image.shape``. While the latter often works,
it may cause problems for small images due to aliasing of spatial
and color-channel axes.
kwargs : ...
Extra arguments to pass to pillow. If a writer doesn't recognise an
option, it is silently ignored. The available options are described
in pillow's `image format documentation
`_
for each writer.
Notes
-----
When writing batches of very narrow (2-4 pixels wide) gray images set
the ``mode`` explicitly to avoid the batch being identified as a colored
image.
"""
if "fps" in kwargs:
raise TypeError(
"The keyword `fps` is no longer supported. Use `duration`"
"(in ms) instead, e.g. `fps=50` == `duration=20` (1000 * 1/50)."
)
extension = self.request.extension or self.request.format_hint
save_args = {
"format": format or Image.registered_extensions()[extension],
}
if isinstance(ndimage, list):
ndimage = np.stack(ndimage, axis=0)
is_batch = True
else:
ndimage = np.asarray(ndimage)
# check if ndimage is a batch of frames/pages (e.g. for writing GIF)
# if mode is given, use it; otherwise fall back to image.ndim only
if is_batch is not None:
pass
elif mode is not None:
is_batch = (
ndimage.ndim > 3 if Image.getmodebands(mode) > 1 else ndimage.ndim > 2
)
elif ndimage.ndim == 2:
is_batch = False
elif ndimage.ndim == 3 and ndimage.shape[-1] == 1:
raise ValueError("Can't write images with one color channel.")
elif ndimage.ndim == 3 and ndimage.shape[-1] in [2, 3, 4]:
# Note: this makes a channel-last assumption
is_batch = False
else:
is_batch = True
if not is_batch:
ndimage = ndimage[None, ...]
pil_frames = list()
for frame in ndimage:
pil_frame = Image.fromarray(frame, mode=mode)
if "bits" in kwargs:
pil_frame = pil_frame.quantize(colors=2 ** kwargs["bits"])
pil_frames.append(pil_frame)
primary_image, other_images = pil_frames[0], pil_frames[1:]
if is_batch:
save_args["save_all"] = True
save_args["append_images"] = other_images
save_args.update(kwargs)
primary_image.save(self._request.get_file(), **save_args)
if self._request._uri_type == URI_BYTES:
file = cast(BytesIO, self._request.get_file())
return file.getvalue()
return None
def get_meta(self, *, index=0) -> Dict[str, Any]:
return self.metadata(index=index, exclude_applied=False)
def metadata(
self, index: int = None, exclude_applied: bool = True
) -> Dict[str, Any]:
"""Read ndimage metadata.
Parameters
----------
index : {integer, None}
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return its
metadata. If index is an ellipsis (...), read and return global
metadata. If index is None, this plugin reads metadata from the
first image of the file (index=0) unless the image is a GIF or APNG,
in which case global metadata is read (index=...).
Returns
-------
metadata : dict
A dictionary of format-specific metadata.
"""
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if isinstance(index, int) and self._image.tell() != index:
self._image.seek(index)
metadata = self._image.info.copy()
metadata["mode"] = self._image.mode
metadata["shape"] = self._image.size
if self._image.mode == "P":
metadata["palette"] = self._image.palette
if self._image.getexif():
exif_data = {
ExifTags.TAGS.get(key, "unknown"): value
for key, value in dict(self._image.getexif()).items()
}
exif_data.pop("unknown", None)
metadata.update(exif_data)
if exclude_applied:
metadata.pop("Orientation", None)
return metadata
def properties(self, index: int = None) -> ImageProperties:
"""Standardized ndimage metadata
Parameters
----------
index : int
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return its
properties. If index is an ellipsis (...), read and return the
properties of all ndimages in the file stacked along a new batch
dimension. If index is None, this plugin reads and returns the
properties of the first image (index=0) unless the image is a GIF or
APNG, in which case it reads and returns the properties all images
(index=...).
Returns
-------
properties : ImageProperties
A dataclass filled with standardized image metadata.
Notes
-----
This does not decode pixel data and is 394fast for large images.
"""
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if index is Ellipsis:
self._image.seek(0)
else:
self._image.seek(index)
if self._image.format == "GIF":
# GIF mode is determined by pallette
mode = self._image.palette.mode
else:
mode = self._image.mode
width: int = self._image.width
height: int = self._image.height
shape: Tuple[int, ...] = (height, width)
n_frames: int = self._image.n_frames
if index is ...:
shape = (n_frames, *shape)
dummy = np.asarray(Image.new(mode, (1, 1)))
pil_shape: Tuple[int, ...] = dummy.shape
if len(pil_shape) > 2:
shape = (*shape, *pil_shape[2:])
return ImageProperties(
shape=shape,
dtype=dummy.dtype,
is_batch=True if index is Ellipsis else False,
)