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70 lines
2.1 KiB
70 lines
2.1 KiB
# Copyright (c) OpenMMLab. All rights reserved.
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from unittest.mock import MagicMock
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import pytest
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from mmcv import Config
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from numpy.testing import assert_almost_equal
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from mmpose.datasets import DATASETS
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from tests.utils.data_utils import convert_db_to_output
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def test_deepfashion_dataset():
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dataset = 'DeepFashionDataset'
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dataset_info = Config.fromfile(
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'configs/_base_/datasets/deepfashion_full.py').dataset_info
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# test JHMDB datasets
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dataset_class = DATASETS.get(dataset)
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dataset_class.load_annotations = MagicMock()
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dataset_class.coco = MagicMock()
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channel_cfg = dict(
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num_output_channels=8,
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dataset_joints=8,
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dataset_channel=[
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[0, 1, 2, 3, 4, 5, 6, 7],
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],
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inference_channel=[0, 1, 2, 3, 4, 5, 6, 7])
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data_cfg = dict(
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image_size=[192, 256],
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heatmap_size=[48, 64],
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num_output_channels=channel_cfg['num_output_channels'],
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num_joints=channel_cfg['dataset_joints'],
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dataset_channel=channel_cfg['dataset_channel'],
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inference_channel=channel_cfg['inference_channel'],
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soft_nms=False,
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nms_thr=1.0,
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oks_thr=0.9,
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vis_thr=0.2,
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use_gt_bbox=True,
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det_bbox_thr=0.0,
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image_thr=0.0,
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bbox_file='')
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# Test gt bbox
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custom_dataset = dataset_class(
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ann_file='tests/data/fld/test_fld.json',
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img_prefix='tests/data/fld/',
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subset='full',
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data_cfg=data_cfg,
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pipeline=[],
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dataset_info=dataset_info,
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test_mode=True)
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assert custom_dataset.test_mode is True
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assert custom_dataset.dataset_name == 'deepfashion_full'
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image_id = 128
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assert image_id in custom_dataset.img_ids
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assert len(custom_dataset.img_ids) == 2
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_ = custom_dataset[0]
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results = convert_db_to_output(custom_dataset.db)
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infos = custom_dataset.evaluate(results, metric=['PCK', 'EPE', 'AUC'])
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assert_almost_equal(infos['PCK'], 1.0)
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assert_almost_equal(infos['AUC'], 0.95)
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assert_almost_equal(infos['EPE'], 0.0)
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with pytest.raises(KeyError):
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infos = custom_dataset.evaluate(results, metric='mAP')
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