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