forked from PulseFocusPlatform/PulseFocusPlatform
118 lines
4.3 KiB
Python
118 lines
4.3 KiB
Python
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import os
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import yaml
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import logging
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import sys
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# add python path of PadleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 4)))
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if parent_path not in sys.path:
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sys.path.append(parent_path)
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from ppdet.utils.download import get_path
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from ppdet.utils.download import DATASET_HOME
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from ppdet.core.workspace import load_config, merge_config
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from ppdet.data.reader import create_reader
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from ppdet.utils.check import enable_static_mode
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COCO_VAL_URL = 'http://images.cocodataset.org/zips/val2017.zip'
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COCO_VAL_MD5SUM = '442b8da7639aecaf257c1dceb8ba8c80'
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COCO_ANNO_URL = 'http://images.cocodataset.org/annotations/annotations_trainval2017.zip'
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COCO_ANNO_MD5SUM = 'f4bbac642086de4f52a3fdda2de5fa2c'
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FORMAT = '[%(asctime)s-%(filename)s-%(levelname)s:%(message)s]'
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logging.basicConfig(level=logging.INFO, format=FORMAT)
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logger = logging.getLogger(__name__)
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class TestReaderYAML(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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""" setup
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"""
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root_path = os.path.join(DATASET_HOME, 'coco')
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_, _ = get_path(COCO_VAL_URL, root_path, COCO_VAL_MD5SUM)
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_, _ = get_path(COCO_ANNO_URL, root_path, COCO_ANNO_MD5SUM)
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cls.anno_path = 'annotations/instances_val2017.json'
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cls.image_dir = 'val2017'
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cls.root_path = root_path
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@classmethod
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def tearDownClass(cls):
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""" tearDownClass """
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pass
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def test_loader_yaml(self):
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cfg_file = 'ppdet/data/tests/test.yml'
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cfg = load_config(cfg_file)
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data_cfg = '[!COCODataSet {{image_dir: {0}, dataset_dir: {1}, ' \
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'anno_path: {2}, sample_num: 10}}]'.format(
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self.image_dir, self.root_path, self.anno_path)
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dataset_ins = yaml.load(data_cfg, Loader=yaml.Loader)
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update_train_cfg = {'TrainReader': {'dataset': dataset_ins[0]}}
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update_test_cfg = {'EvalReader': {'dataset': dataset_ins[0]}}
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merge_config(update_train_cfg)
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merge_config(update_test_cfg)
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reader = create_reader(cfg['TrainReader'], 10)()
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for samples in reader:
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for sample in samples:
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im_shape = sample[0].shape
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self.assertEqual(im_shape[0], 3)
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self.assertEqual(im_shape[1] % 32, 0)
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self.assertEqual(im_shape[2] % 32, 0)
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im_info_shape = sample[1].shape
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self.assertEqual(im_info_shape[-1], 3)
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im_id_shape = sample[2].shape
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self.assertEqual(im_id_shape[-1], 1)
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gt_bbox_shape = sample[3].shape
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self.assertEqual(gt_bbox_shape[-1], 4)
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gt_class_shape = sample[4].shape
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self.assertEqual(gt_class_shape[-1], 1)
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self.assertEqual(gt_class_shape[0], gt_bbox_shape[0])
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is_crowd_shape = sample[5].shape
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self.assertEqual(is_crowd_shape[-1], 1)
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self.assertEqual(is_crowd_shape[0], gt_bbox_shape[0])
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mask = sample[6]
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self.assertEqual(len(mask), gt_bbox_shape[0])
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self.assertEqual(mask[0][0].shape[-1], 2)
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reader = create_reader(cfg['EvalReader'], 10)()
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for samples in reader:
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for sample in samples:
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im_shape = sample[0].shape
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self.assertEqual(im_shape[0], 3)
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self.assertEqual(im_shape[1] % 32, 0)
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self.assertEqual(im_shape[2] % 32, 0)
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im_info_shape = sample[1].shape
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self.assertEqual(im_info_shape[-1], 3)
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im_id_shape = sample[2].shape
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self.assertEqual(im_id_shape[-1], 1)
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if __name__ == '__main__':
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enable_static_mode()
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unittest.main()
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