Source code for tensorbay.opendataset.DogsVsCats.loader

#!/usr/bin/env python3
#
# Copyright 2021 Graviti. Licensed under MIT License.
#
# pylint: disable=invalid-name

"""Dataloader of DogsVsCats dataset."""

import os

from tensorbay.dataset import Data, Dataset
from tensorbay.label import Classification
from tensorbay.opendataset._utility import glob

DATASET_NAME = "DogsVsCats"
_SEGMENTS = {"train": True, "test": False}


[docs]def DogsVsCats(path: str) -> Dataset: """`Dogs vs Cats <https://www.kaggle.com/c/dogs-vs-cats>`_ dataset. The file structure should be like:: <path> train/ cat.0.jpg ... dog.0.jpg ... test/ 1000.jpg 1001.jpg ... Arguments: path: The root directory of the dataset. Returns: Loaded :class:`~tensorbay.dataset.dataset.Dataset` instance. """ root_path = os.path.abspath(os.path.expanduser(path)) dataset = Dataset(DATASET_NAME) dataset.load_catalog(os.path.join(os.path.dirname(__file__), "catalog.json")) for segment_name, is_labeled in _SEGMENTS.items(): segment = dataset.create_segment(segment_name) image_paths = glob(os.path.join(root_path, segment_name, "*.jpg")) for image_path in image_paths: data = Data(image_path) if is_labeled: data.label.classification = Classification(os.path.basename(image_path)[:3]) segment.append(data) return dataset