forked from mindspore-Ecosystem/mindspore
233 lines
9.1 KiB
Python
233 lines
9.1 KiB
Python
# Copyright 2020-2022 Huawei Technologies Co., Ltd
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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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# ==============================================================================
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"""
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Testing the bounding box augment op in DE
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"""
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import mindspore.log as logger
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import mindspore.dataset as ds
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import mindspore.dataset.vision as c_vision
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from util import config_get_set_seed, config_get_set_num_parallel_workers, save_and_check_md5, \
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helper_perform_ops_bbox, helper_test_visual_bbox, helper_invalid_bounding_box_test, \
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helper_perform_ops_bbox_edgecase_float
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GENERATE_GOLDEN = False
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# updated VOC dataset with correct annotations
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DATA_DIR = "../data/dataset/testVOC2012_2"
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DATA_DIR_2 = ["../data/dataset/testCOCO/train/",
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"../data/dataset/testCOCO/annotations/train.json"] # DATA_DIR, ANNOTATION_DIR
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def test_bounding_box_augment_with_rotation_op(plot_vis=False):
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"""
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Feature: BoundingBoxAugment op
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Description: Prints images and bboxes side by side with and without aug to compare by passing rotation op
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Expectation: Passes the md5 check test
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"""
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logger.info("test_bounding_box_augment_with_rotation_op")
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original_seed = config_get_set_seed(0)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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# Ratio is set to 1 to apply rotation on all bounding boxes.
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test_op = c_vision.BoundingBoxAugment(c_vision.RandomRotation(90), 1)
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# map to apply ops
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data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
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data_voc2 = data_voc2.project(["image", "bbox"])
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filename = "bounding_box_augment_rotation_c_result.npz"
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save_and_check_md5(data_voc2, filename, generate_golden=GENERATE_GOLDEN)
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helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)
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# Restore config setting
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ds.config.set_seed(original_seed)
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ds.config.set_num_parallel_workers(original_num_parallel_workers)
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def test_bounding_box_augment_with_crop_op(plot_vis=False):
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"""
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Feature: BoundingBoxAugment op
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Description: Prints images and bboxes side by side with and without aug to compare by passing crop op
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Expectation: Passes the md5 check test
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"""
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logger.info("test_bounding_box_augment_with_crop_op")
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original_seed = config_get_set_seed(0)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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# Ratio is set to 0.9 to apply RandomCrop of size (50, 50) on 90% of the bounding boxes.
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test_op = c_vision.BoundingBoxAugment(c_vision.RandomCrop(50), 0.9)
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# map to apply ops
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data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
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data_voc2 = data_voc2.project(["image", "bbox"])
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filename = "bounding_box_augment_crop_c_result.npz"
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save_and_check_md5(data_voc2, filename, generate_golden=GENERATE_GOLDEN)
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helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)
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# Restore config setting
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ds.config.set_seed(original_seed)
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ds.config.set_num_parallel_workers(original_num_parallel_workers)
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def test_bounding_box_augment_valid_ratio_c(plot_vis=False):
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"""
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Feature: BoundingBoxAugment op
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Description: Prints images and bboxes side by side with and without aug to compare with valid ratio
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Expectation: Passes the md5 check test
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"""
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logger.info("test_bounding_box_augment_valid_ratio_c")
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original_seed = config_get_set_seed(1)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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test_op = c_vision.BoundingBoxAugment(
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c_vision.RandomHorizontalFlip(1), 0.9)
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# map to apply ops
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data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
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data_voc2 = data_voc2.project(["image", "bbox"])
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filename = "bounding_box_augment_valid_ratio_c_result.npz"
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save_and_check_md5(data_voc2, filename, generate_golden=GENERATE_GOLDEN)
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helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)
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# Restore config setting
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ds.config.set_seed(original_seed)
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ds.config.set_num_parallel_workers(original_num_parallel_workers)
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def test_bounding_box_augment_op_coco_c(plot_vis=False):
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"""
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Feature: BoundingBoxAugment op
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Description: Prints images and bboxes side by side with and without BoundingBoxAugment Op applied with CocoDataset
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Expectation: Passes the test
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"""
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logger.info("test_bounding_box_augment_op_coco_c")
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data_coco1 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection",
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decode=True, shuffle=False)
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data_coco2 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection",
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decode=True, shuffle=False)
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test_op = c_vision.BoundingBoxAugment(c_vision.RandomHorizontalFlip(1), 1)
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data_coco2 = helper_perform_ops_bbox(data_coco2, test_op)
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helper_test_visual_bbox(plot_vis, data_coco1, data_coco2)
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def test_bounding_box_augment_valid_edge_c(plot_vis=False):
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"""
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Feature: BoundingBoxAugment op
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Description: Prints images and bboxes side by side with and without aug to compare with valid edge case
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Expectation: Passes the md5 check test on edge case where box covering full image
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"""
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logger.info("test_bounding_box_augment_valid_edge_c")
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original_seed = config_get_set_seed(1)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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test_op = c_vision.BoundingBoxAugment(c_vision.RandomHorizontalFlip(1), 1)
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# map to apply ops
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data_voc1 = helper_perform_ops_bbox_edgecase_float(data_voc1)
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data_voc2 = helper_perform_ops_bbox_edgecase_float(data_voc2)
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data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
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data_voc2 = data_voc2.project(["image", "bbox"])
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filename = "bounding_box_augment_valid_edge_c_result.npz"
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save_and_check_md5(data_voc2, filename, generate_golden=GENERATE_GOLDEN)
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helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)
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# Restore config setting
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ds.config.set_seed(original_seed)
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ds.config.set_num_parallel_workers(original_num_parallel_workers)
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def test_bounding_box_augment_invalid_ratio_c():
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"""
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Feature: BoundingBoxAugment op
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Description: Test BoundingBoxAugment op with invalid input ratio
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Expectation: Error is raised as expected
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"""
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logger.info("test_bounding_box_augment_invalid_ratio_c")
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data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
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usage="train", shuffle=False, decode=True)
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try:
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# ratio range is from 0 - 1
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test_op = c_vision.BoundingBoxAugment(
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c_vision.RandomHorizontalFlip(1), 1.5)
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# map to apply ops
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data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
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except ValueError as error:
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logger.info("Got an exception in DE: {}".format(str(error)))
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assert "Input ratio is not within the required interval of [0.0, 1.0]." in str(
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error)
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def test_bounding_box_augment_invalid_bounds_c():
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"""
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Feature: BoundingBoxAugment op
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Description: Test BoundingBoxAugment op with invalid bboxes
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Expectation: Correct error is thrown as expected
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"""
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logger.info("test_bounding_box_augment_invalid_bounds_c")
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test_op = c_vision.BoundingBoxAugment(c_vision.RandomHorizontalFlip(1),
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1)
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helper_invalid_bounding_box_test(DATA_DIR, test_op)
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if __name__ == "__main__":
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# set to false to not show plots
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test_bounding_box_augment_with_rotation_op(plot_vis=False)
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test_bounding_box_augment_with_crop_op(plot_vis=False)
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test_bounding_box_augment_op_coco_c(plot_vis=False)
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test_bounding_box_augment_valid_ratio_c(plot_vis=False)
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test_bounding_box_augment_valid_edge_c(plot_vis=False)
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test_bounding_box_augment_invalid_ratio_c()
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test_bounding_box_augment_invalid_bounds_c()
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