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