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# Copyright (C) 2021-2024, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from pathlib import Path
from typing import List, Sequence, Union
import numpy as np
from doctr.file_utils import requires_package
from doctr.utils.common_types import AbstractFile
from .html import read_html
from .image import read_img_as_numpy
from .pdf import read_pdf
__all__ = ["DocumentFile"]
class DocumentFile:
"""Read a document from multiple extensions"""
@classmethod
def from_pdf(cls, file: AbstractFile, **kwargs) -> List[np.ndarray]:
"""Read a PDF file
>>> from doctr.io import DocumentFile
>>> doc = DocumentFile.from_pdf("path/to/your/doc.pdf")
Args:
----
file: the path to the PDF file or a binary stream
**kwargs: additional parameters to :meth:`pypdfium2.PdfPage.render`
Returns:
-------
the list of pages decoded as numpy ndarray of shape H x W x 3
"""
return read_pdf(file, **kwargs)
@classmethod
def from_url(cls, url: str, **kwargs) -> List[np.ndarray]:
"""Interpret a web page as a PDF document
>>> from doctr.io import DocumentFile
>>> doc = DocumentFile.from_url("https://www.yoursite.com")
Args:
----
url: the URL of the target web page
**kwargs: additional parameters to :meth:`pypdfium2.PdfPage.render`
Returns:
-------
the list of pages decoded as numpy ndarray of shape H x W x 3
"""
requires_package(
"weasyprint",
"`.from_url` requires weasyprint installed.\n"
+ "Installation instructions: https://doc.courtbouillon.org/weasyprint/stable/first_steps.html#installation",
)
pdf_stream = read_html(url)
return cls.from_pdf(pdf_stream, **kwargs)
@classmethod
def from_images(cls, files: Union[Sequence[AbstractFile], AbstractFile], **kwargs) -> List[np.ndarray]:
"""Read an image file (or a collection of image files) and convert it into an image in numpy format
>>> from doctr.io import DocumentFile
>>> pages = DocumentFile.from_images(["path/to/your/page1.png", "path/to/your/page2.png"])
Args:
----
files: the path to the image file or a binary stream, or a collection of those
**kwargs: additional parameters to :meth:`doctr.io.image.read_img_as_numpy`
Returns:
-------
the list of pages decoded as numpy ndarray of shape H x W x 3
"""
if isinstance(files, (str, Path, bytes)):
files = [files]
return [read_img_as_numpy(file, **kwargs) for file in files]
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