Source code for tensorbay.opendataset.CoinImage.loader

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

"""Dataloader of CoinImage dataset."""

import csv
import os
from typing import Dict

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

DATASET_NAME = "CoinImage"


[docs]def CoinImage(path: str) -> Dataset: """`Coin Image <https://cvl.tuwien.ac.at/research/cvl-databases/coin-image-dataset/>`_ dataset. The file structure should be like:: <path> classes.csv <imagename>.png ... 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")) segment = dataset.create_segment() csv_path = os.path.join(root_path, "classes.csv") with open(csv_path, encoding="utf-8") as fp: reader = csv.reader(fp, delimiter=";") mapping: Dict[str, str] = dict(row for row in reader) # type: ignore[arg-type, misc] image_paths = glob(os.path.join(root_path, "*.png")) for image_path in image_paths: data = Data(image_path) filename = os.path.basename(image_path) class_id = filename[5:].split("_", 1)[0] data.label.classification = Classification(category=mapping[class_id]) segment.append(data) return dataset