image_sample_data.py

#     Copyright (C) 2023  Coretex LLC
 
#     This file is part of Coretex.ai
 
#     This program is free software: you can redistribute it and/or modify
#     it under the terms of the GNU Affero General Public License as
#     published by the Free Software Foundation, either version 3 of the
#     License, or (at your option) any later version.
 
#     This program is distributed in the hope that it will be useful,
#     but WITHOUT ANY WARRANTY; without even the implied warranty of
#     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#     GNU Affero General Public License for more details.
 
#     You should have received a copy of the GNU Affero General Public License
#     along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
from typing import Final, Optional
from pathlib import Path
 
import json
 
from PIL import Image, ImageOps
from PIL.Image import Image as PILImage
 
import numpy as np
 
from .image_format import ImageFormat
from ...annotation import CoretexImageAnnotation, ImageDatasetClasses
 
 
def _findImage(path: Path) -> Path:
    for format in ImageFormat:
        imagePaths = list(path.glob(f"*.{format.extension}"))
        imagePaths = [path for path in imagePaths if not "thumb" in str(path)]
 
        if len(imagePaths) > 0:
            return Path(imagePaths[0])
 
    raise RuntimeError
 
 
def _readImageData(path: Path) -> np.ndarray:
    image = ImageOps.exif_transpose(Image.open(path))
    if not isinstance(image, PILImage):
        raise TypeError(f"Expected \"PIL.Image.Image\" recieved \"{type(image)}\"")
 
    if image.mode != "RGB":
        image = image.convert("RGB")
 
    imageData = np.frombuffer(image.tobytes(), dtype = np.uint8)
    imageData = imageData.reshape((image.size[1], image.size[0], 3))
 
    return imageData
 
 
def _readAnnotationData(path: Path) -> CoretexImageAnnotation:
    with open(path, "r") as annotationsFile:
        return CoretexImageAnnotation.decode(
            json.load(annotationsFile)
        )
 
 
class AnnotatedImageSampleData:
 
    """
        Contains image data as well as its annotation\n
        Annotation is expected to be in Coretex.ai format
    """
 
    def __init__(self, path: Path) -> None:
        self.image: Final = _readImageData(_findImage(path))
        self.annotationannotation: Optional[CoretexImageAnnotation] = None
 
        annotationPath = path / "annotations.json"
        if annotationPath.exists():
            self.annotationannotation = _readAnnotationData(annotationPath)
 
    def extractSegmentationMask(self, classes: ImageDatasetClasses) -> np.ndarray:
        """
            Generates segmentation mask for the provided classes
 
            Parameters
            ----------
            classes : ImageDatasetClasses
                list of dataset classes
 
            Returns
            -------
            np.ndarray -> segmentation mask represented as np.ndarray
        """
 
        if self.annotationannotation is None:
            raise ValueError
 
        return self.annotationannotation.extractSegmentationMask(classes)