import numpy as np

from unittest import TestCase

from datumaro.components.extractor import (Extractor, DatasetItem,
    AnnotationType, Bbox, LabelCategories,
)
from datumaro.plugins.yolo_format.importer import YoloImporter
from datumaro.plugins.yolo_format.converter import YoloConverter
from datumaro.util.test_utils import TestDir, compare_datasets


class YoloFormatTest(TestCase):
    def test_can_save_and_load(self):
        class TestExtractor(Extractor):
            def __iter__(self):
                return iter([
                    DatasetItem(id=1, subset='train', image=np.ones((8, 8, 3)),
                        annotations=[
                            Bbox(0, 2, 4, 2, label=2),
                            Bbox(0, 1, 2, 3, label=4),
                        ]),
                    DatasetItem(id=2, subset='train', image=np.ones((10, 10, 3)),
                        annotations=[
                            Bbox(0, 2, 4, 2, label=2),
                            Bbox(3, 3, 2, 3, label=4),
                            Bbox(2, 1, 2, 3, label=4),
                        ]),

                    DatasetItem(id=3, subset='valid', image=np.ones((8, 8, 3)),
                        annotations=[
                            Bbox(0, 1, 5, 2, label=2),
                            Bbox(0, 2, 3, 2, label=5),
                            Bbox(0, 2, 4, 2, label=6),
                            Bbox(0, 7, 3, 2, label=7),
                        ]),
                ])

            def categories(self):
                label_categories = LabelCategories()
                for i in range(10):
                    label_categories.add('label_' + str(i))
                return {
                    AnnotationType.label: label_categories,
                }

        with TestDir() as test_dir:
            source_dataset = TestExtractor()

            YoloConverter(save_images=True)(source_dataset, test_dir)
            parsed_dataset = YoloImporter()(test_dir).make_dataset()

            compare_datasets(self, source_dataset, parsed_dataset)