image_classification/pt/src/datasets/flowers102.py

# /*---------------------------------------------------------------------------------------------
#  * Copyright (c) 2025 STMicroelectronics.
#  * All rights reserved.
#  *
#  * Copyright (c) Soumith Chintala 2016, All rights reserved., with a BSD-3 license
#  *
#  * This software is licensed under terms that can be found in the LICENSE file in
#  * the root directory of this software component.
#  * If no LICENSE file comes with this software, it is provided AS-IS.
#  *--------------------------------------------------------------------------------------------*/

from pathlib import Path

import PIL.Image
from torchvision.datasets.utils import (
    check_integrity,
    download_and_extract_archive,
    download_url,
    verify_str_arg,
)
from torchvision.datasets.vision import VisionDataset


class Flowers102(VisionDataset):
    # Taken from https://github.com/pytorch/vision/blob/HEAD/torchvision/datasets/flowers102.py
    # Added for compatibility with old torchvision versions

    _download_url_prefix = "https://www.robots.ox.ac.uk/~vgg/data/flowers/102/"
    _file_dict = {  # filename, md5
        "image": ("102flowers.tgz", "52808999861908f626f3c1f4e79d11fa"),
        "label": ("imagelabels.mat", "e0620be6f572b9609742df49c70aed4d"),
        "setid": ("setid.mat", "a5357ecc9cb78c4bef273ce3793fc85c"),
    }
    _splits_map = {"train": "trnid", "val": "valid", "test": "tstid"}

    def __init__(
        self,
        root: str,
        split: str = "train",
        transform=None,
        target_transform=None,
        download: bool = False,
    ) -> None:
        super().__init__(root, transform=transform, target_transform=target_transform)
        self._split = verify_str_arg(split, "split", ("train", "val", "test"))
        self._base_folder = Path(self.root) / "flowers-102"
        #self._base_folder = Path(self.root) # Latest changes by nikhil
        self._images_folder = self._base_folder / "jpg"

        if download:
            self.download()

        if not self._check_integrity():
            raise RuntimeError(
                "Dataset not found or corrupted. You can use download=True to download it"
            )

        from scipy.io import loadmat

        set_ids = loadmat(
            self._base_folder / self._file_dict["setid"][0], squeeze_me=True
        )
        image_ids = set_ids[self._splits_map[self._split]].tolist()

        labels = loadmat(
            self._base_folder / self._file_dict["label"][0], squeeze_me=True
        )
        image_id_to_label = dict(enumerate((labels["labels"] - 1).tolist(), 1))

        self._labels = []
        self._image_files = []
        for image_id in image_ids:
            self._labels.append(image_id_to_label[image_id])
            self._image_files.append(self._images_folder / f"image_{image_id:05d}.jpg")

        self.classes = set(self._labels)

    def __len__(self) -> int:
        return len(self._image_files)

    def __getitem__(self, idx):
        image_file, label = self._image_files[idx], self._labels[idx]
        image = PIL.Image.open(image_file).convert("RGB")

        if self.transform:
            image = self.transform(image)

        if self.target_transform:
            label = self.target_transform(label)

        return image, label

    def extra_repr(self):
        return f"split={self._split}"

    def _check_integrity(self):
        if not (self._images_folder.exists() and self._images_folder.is_dir()):
            return False

        for id in ["label", "setid"]:
            filename, md5 = self._file_dict[id]
            if not check_integrity(str(self._base_folder / filename), md5):
                return False
        return True

    def download(self):
        if self._check_integrity():
            return
        download_and_extract_archive(
            f"{self._download_url_prefix}{self._file_dict['image'][0]}",
            str(self._base_folder),
            md5=self._file_dict["image"][1],
        )
        for id in ["label", "setid"]:
            filename, md5 = self._file_dict[id]
            download_url(
                self._download_url_prefix + filename, str(self._base_folder), md5=md5
            )