from __future__ import annotations
import logging
from io import BytesIO
from pathlib import Path
from typing import Optional, Sequence, Union
from PIL import Image
import meerkat.tools.docs as docs
from meerkat.columns.deferred.file import FILE_SHARED_DOCS, FileColumn
from meerkat.interactive.formatter import ImageFormatterGroup
from meerkat.interactive.formatter.base import deferred_formatter_group
logger = logging.getLogger(__name__)
def load_image(f: Union[str, BytesIO, Path]):
img = Image.open(f)
return img.convert("RGB")
[docs]@docs.doc(source=FILE_SHARED_DOCS)
def image(
filepaths: Sequence[str],
base_dir: Optional[str] = None,
downloader: Union[callable, str] = None,
loader: callable = load_image,
cache_dir: str = None,
):
"""Create a :class:`FileColumn` where each cell represents an image stored
on disk. The underlying data is a :class:`ScalarColumn` of strings, where
each string is the path to an image.
Args:
filepaths (Sequence[str]): A list of filepaths to images.
${loader}
${base_dir}
${downloader}
${fallback_downloader}
${cache_dir}
"""
return FileColumn(
filepaths,
type="image",
base_dir=base_dir,
loader=loader,
downloader=downloader,
cache_dir=cache_dir,
formatters=deferred_formatter_group(ImageFormatterGroup()),
)
[docs]class ImageColumn(FileColumn):
"""DEPRECATED A column where each cell represents an image stored on disk.
The underlying data is a `PandasSeriesColumn` of strings, where each string
is the path to an image. The column materializes the images into memory
when indexed. If the column is lazy indexed with the ``lz`` indexer, the
images are not materialized and an ``ImageCell`` or an ``ImageColumn`` is
returned instead.
Args:
data (Sequence[str]): A list of filepaths to images.
transform (callable): A function that transforms the image (e.g.
``torchvision.transforms.functional.center_crop``).
.. warning::
In order for the column to be serializable, the transform function must
be pickleable.
loader (callable): A callable with signature ``def loader(filepath: str) ->
PIL.Image:``. Defaults to ``torchvision.datasets.folder.default_loader``.
.. warning::
In order for the column to be serializable with ``write()``, the loader
function must be pickleable.
base_dir (str): A base directory that the paths in ``data`` are relative to. If
``None``, the paths are assumed to be absolute.
"""
@classmethod
def default_loader(cls, *args, **kwargs):
return load_image(*args, **kwargs)
