Source code for tensorbay.opendataset.VOC2012Detection.loader
#!/usr/bin/env python3
#
# Copyright 2021 Graviti. Licensed under MIT License.
#
# pylint: disable=invalid-name
"""Dataloader of VOC2012Detection dataset."""
import os
from tensorbay.dataset import Dataset
from tensorbay.opendataset._utility import get_boolean_attributes, get_voc_detection_data
DATASET_NAME = "VOC2012Detection"
_SEGMENT_NAMES = ("train", "val")
[docs]def VOC2012Detection(path: str) -> Dataset:
"""`VOC2012Detection <http://host.robots.ox.ac.uk/pascal/VOC/voc2012/>`_ dataset.
The file structure should be like::
<path>
Annotations/
<image_name>.xml
...
JPEGImages/
<image_name>.jpg
...
ImageSets/
Main/
train.txt
val.txt
...
...
...
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))
annotation_path = os.path.join(root_path, "Annotations")
image_path = os.path.join(root_path, "JPEGImages")
main_path = os.path.join(root_path, "ImageSets", "Main")
dataset = Dataset(DATASET_NAME)
dataset.load_catalog(os.path.join(os.path.dirname(__file__), "catalog.json"))
boolean_attributes = get_boolean_attributes(dataset.catalog.box2d)
for segment_name in _SEGMENT_NAMES:
segment = dataset.create_segment(segment_name)
with open(os.path.join(main_path, f"{segment_name}.txt"), encoding="utf-8") as fp:
for stem in fp:
segment.append(
get_voc_detection_data(
stem.rstrip(), image_path, annotation_path, boolean_attributes
)
)
return dataset