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