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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 Optional, Tuple
import cv2
import numpy as np
from doctr.utils.common_types import AbstractFile
__all__ = ["read_img_as_numpy"]
def read_img_as_numpy(
file: AbstractFile,
output_size: Optional[Tuple[int, int]] = None,
rgb_output: bool = True,
) -> np.ndarray:
"""Read an image file into numpy format
>>> from doctr.io import read_img_as_numpy
>>> page = read_img_as_numpy("path/to/your/doc.jpg")
Args:
----
file: the path to the image file
output_size: the expected output size of each page in format H x W
rgb_output: whether the output ndarray channel order should be RGB instead of BGR.
Returns:
-------
the page decoded as numpy ndarray of shape H x W x 3
"""
if isinstance(file, (str, Path)):
if not Path(file).is_file():
raise FileNotFoundError(f"unable to access {file}")
img = cv2.imread(str(file), cv2.IMREAD_COLOR)
elif isinstance(file, bytes):
_file: np.ndarray = np.frombuffer(file, np.uint8)
img = cv2.imdecode(_file, cv2.IMREAD_COLOR)
else:
raise TypeError("unsupported object type for argument 'file'")
# Validity check
if img is None:
raise ValueError("unable to read file.")
# Resizing
if isinstance(output_size, tuple):
img = cv2.resize(img, output_size[::-1], interpolation=cv2.INTER_LINEAR)
# Switch the channel order
if rgb_output:
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
return img
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