diff --git a/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_coco_result.npz b/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_coco_result.npz new file mode 100644 index 0000000000..db62d6509e Binary files /dev/null and b/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_coco_result.npz differ diff --git a/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_voc_result.npz b/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_voc_result.npz new file mode 100644 index 0000000000..75f4447ded Binary files /dev/null and b/tests/ut/data/dataset/golden/random_resize_with_bbox_op_01_c_voc_result.npz differ diff --git a/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_coco_result.npz b/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_coco_result.npz new file mode 100644 index 0000000000..999c15e5f3 Binary files /dev/null and b/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_coco_result.npz differ diff --git a/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_voc_result.npz b/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_voc_result.npz new file mode 100644 index 0000000000..ca64884937 Binary files /dev/null and b/tests/ut/data/dataset/golden/resize_with_bbox_op_01_c_voc_result.npz differ diff --git a/tests/ut/python/dataset/test_random_resize_with_bbox.py b/tests/ut/python/dataset/test_random_resize_with_bbox.py new file mode 100644 index 0000000000..8e2dab33e1 --- /dev/null +++ b/tests/ut/python/dataset/test_random_resize_with_bbox.py @@ -0,0 +1,215 @@ +# Copyright 2020 Huawei Technologies Co., Ltd +# +# 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. +# ============================================================================== +""" +Testing the random resize with bounding boxes op in DE +""" +import numpy as np +import mindspore.dataset as ds +import mindspore.dataset.transforms.vision.c_transforms as c_vision + +from mindspore import log as logger +from util import visualize_with_bounding_boxes, InvalidBBoxType, check_bad_bbox, \ + config_get_set_seed, config_get_set_num_parallel_workers, save_and_check_md5 + +GENERATE_GOLDEN = False + +DATA_DIR = "../data/dataset/testVOC2012_2" +DATA_DIR_2 = ["../data/dataset/testCOCO/train/", + "../data/dataset/testCOCO/annotations/train.json"] # DATA_DIR, ANNOTATION_DIR + + +def test_random_resize_with_bbox_op_voc_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without RandomResizeWithBBox Op applied + testing with VOC dataset + """ + logger.info("test_random_resize_with_bbox_op_voc_c") + original_seed = config_get_set_seed(123) + original_num_parallel_workers = config_get_set_num_parallel_workers(1) + # Load dataset + dataVoc1 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + test_op = c_vision.RandomResizeWithBBox(100) + + # map to apply ops + dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[test_op]) + + filename = "random_resize_with_bbox_op_01_c_voc_result.npz" + save_and_check_md5(dataVoc2, filename, generate_golden=GENERATE_GOLDEN) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataVoc1.create_dict_iterator(), dataVoc2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp) + + # Restore config setting + ds.config.set_seed(original_seed) + ds.config.set_num_parallel_workers(original_num_parallel_workers) + + +def test_random_resize_with_bbox_op_rand_coco_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without RandomResizeWithBBox Op applied, + tests with MD5 check, expected to pass + testing with COCO dataset + """ + logger.info("test_random_resize_with_bbox_op_rand_coco_c") + original_seed = config_get_set_seed(231) + original_num_parallel_workers = config_get_set_num_parallel_workers(1) + + # Load dataset + dataCoco1 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection", + decode=True, shuffle=False) + + dataCoco2 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection", + decode=True, shuffle=False) + + test_op = c_vision.RandomResizeWithBBox(200) + + # map to apply ops + + dataCoco2 = dataCoco2.map(input_columns=["image", "bbox"], + output_columns=["image", "bbox"], + columns_order=["image", "bbox"], + operations=[test_op]) + + filename = "random_resize_with_bbox_op_01_c_coco_result.npz" + save_and_check_md5(dataCoco2, filename, generate_golden=GENERATE_GOLDEN) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataCoco1.create_dict_iterator(), dataCoco2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp, annot_name="bbox") + + # Restore config setting + ds.config.set_seed(original_seed) + ds.config.set_num_parallel_workers(original_num_parallel_workers) + + +def test_random_resize_with_bbox_op_edge_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without RandomresizeWithBBox Op applied, + applied on dynamically generated edge case, expected to pass. edge case is when bounding + box has dimensions as the image itself. + """ + logger.info("test_random_resize_with_bbox_op_edge_c") + dataVoc1 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + test_op = c_vision.RandomResizeWithBBox(500) + + # maps to convert data into valid edge case data + dataVoc1 = dataVoc1.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[lambda img, bboxes: ( + img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype))]) + + dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[lambda img, bboxes: ( + img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype)), test_op]) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataVoc1.create_dict_iterator(), dataVoc2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp) + + +def test_random_resize_with_bbox_op_invalid_c(): + """ + Test RandomResizeWithBBox Op on invalid constructor parameters, expected to raise ValueError + """ + logger.info("test_random_resize_with_bbox_op_invalid_c") + + try: + # zero value for resize + c_vision.RandomResizeWithBBox(0) + + except ValueError as err: + logger.info("Got an exception in DE: {}".format(str(err))) + assert "Input is not" in str(err) + + try: + # one of the size values is zero + c_vision.RandomResizeWithBBox((0, 100)) + + except ValueError as err: + logger.info("Got an exception in DE: {}".format(str(err))) + assert "Input is not" in str(err) + + try: + # negative value for resize + c_vision.RandomResizeWithBBox(-10) + + except ValueError as err: + logger.info("Got an exception in DE: {}".format(str(err))) + assert "Input is not" in str(err) + + try: + # invalid input shape + c_vision.RandomResizeWithBBox((100, 100, 100)) + + except TypeError as err: + logger.info("Got an exception in DE: {}".format(str(err))) + assert "Size should be" in str(err) + + +def test_random_resize_with_bbox_op_bad_c(): + """ + Tests RandomResizeWithBBox Op with invalid bounding boxes, expected to catch multiple errors + """ + logger.info("test_random_resize_with_bbox_op_bad_c") + test_op = c_vision.RandomResizeWithBBox((400, 300)) + + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WidthOverflow, "bounding boxes is out of bounds of the image") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.HeightOverflow, "bounding boxes is out of bounds of the image") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.NegativeXY, "min_x") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WrongShape, "4 features") + + +if __name__ == "__main__": + test_random_resize_with_bbox_op_voc_c(plot_vis=False) + test_random_resize_with_bbox_op_rand_coco_c(plot_vis=False) + test_random_resize_with_bbox_op_edge_c(plot_vis=False) + test_random_resize_with_bbox_op_invalid_c() + test_random_resize_with_bbox_op_bad_c() diff --git a/tests/ut/python/dataset/test_resize_with_bbox.py b/tests/ut/python/dataset/test_resize_with_bbox.py new file mode 100644 index 0000000000..5fb957aa32 --- /dev/null +++ b/tests/ut/python/dataset/test_resize_with_bbox.py @@ -0,0 +1,180 @@ +# Copyright 2020 Huawei Technologies Co., Ltd +# +# 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. +# ============================================================================== +""" +Testing the resize with bounding boxes op in DE +""" +import numpy as np +import mindspore.dataset as ds +import mindspore.dataset.transforms.vision.c_transforms as c_vision + +from mindspore import log as logger +from util import visualize_with_bounding_boxes, InvalidBBoxType, check_bad_bbox, \ + save_and_check_md5 + +GENERATE_GOLDEN = False + +DATA_DIR = "../data/dataset/testVOC2012_2" +DATA_DIR_2 = ["../data/dataset/testCOCO/train/", + "../data/dataset/testCOCO/annotations/train.json"] # DATA_DIR, ANNOTATION_DIR + + +def test_resize_with_bbox_op_voc_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without ResizeWithBBox Op applied + testing with VOC dataset + """ + logger.info("test_resize_with_bbox_op_voc_c") + + # Load dataset + dataVoc1 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + test_op = c_vision.ResizeWithBBox(100) + + # map to apply ops + dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[test_op]) + + filename = "resize_with_bbox_op_01_c_voc_result.npz" + save_and_check_md5(dataVoc2, filename, generate_golden=GENERATE_GOLDEN) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataVoc1.create_dict_iterator(), dataVoc2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp) + + +def test_resize_with_bbox_op_coco_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without ResizeWithBBox Op applied, + tests with MD5 check, expected to pass + Testing with COCO dataset + """ + logger.info("test_resize_with_bbox_op_coco_c") + + # Load dataset + dataCOCO1 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection", + decode=True, shuffle=False) + + dataCOCO2 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection", + decode=True, shuffle=False) + + test_op = c_vision.ResizeWithBBox(200) + + # map to apply ops + + dataCOCO2 = dataCOCO2.map(input_columns=["image", "bbox"], + output_columns=["image", "bbox"], + columns_order=["image", "bbox"], + operations=[test_op]) + + filename = "resize_with_bbox_op_01_c_coco_result.npz" + save_and_check_md5(dataCOCO2, filename, generate_golden=GENERATE_GOLDEN) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataCOCO1.create_dict_iterator(), dataCOCO2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp, annot_name="bbox") + + +def test_resize_with_bbox_op_edge_c(plot_vis=False): + """ + Prints images and bboxes side by side with and without ResizeWithBBox Op applied, + applied on dynamically generated edge case, expected to pass. edge case is when bounding + box has dimensions as the image itself. + """ + logger.info("test_resize_with_bbox_op_edge_c") + dataVoc1 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", + decode=True, shuffle=False) + + test_op = c_vision.ResizeWithBBox(500) + + # maps to convert data into valid edge case data + dataVoc1 = dataVoc1.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[lambda img, bboxes: ( + img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype))]) + + dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"], + output_columns=["image", "annotation"], + columns_order=["image", "annotation"], + operations=[lambda img, bboxes: ( + img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype)), test_op]) + + unaugSamp, augSamp = [], [] + + for unAug, Aug in zip(dataVoc1.create_dict_iterator(), dataVoc2.create_dict_iterator()): + unaugSamp.append(unAug) + augSamp.append(Aug) + + if plot_vis: + visualize_with_bounding_boxes(unaugSamp, augSamp) + + +def test_resize_with_bbox_op_invalid_c(): + """ + Test ResizeWithBBox Op on invalid constructor parameters, expected to raise ValueError + """ + logger.info("test_resize_with_bbox_op_invalid_c") + + try: + # invalid interpolation value + c_vision.ResizeWithBBox(400, interpolation="invalid") + + except ValueError as err: + logger.info("Got an exception in DE: {}".format(str(err))) + assert "interpolation" in str(err) + + +def test_resize_with_bbox_op_bad_c(): + """ + Tests ResizeWithBBox Op with invalid bounding boxes, expected to catch multiple errors + """ + logger.info("test_resize_with_bbox_op_bad_c") + test_op = c_vision.ResizeWithBBox((200, 300)) + + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WidthOverflow, "bounding boxes is out of bounds of the image") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.HeightOverflow, "bounding boxes is out of bounds of the image") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.NegativeXY, "min_x") + data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False) + check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WrongShape, "4 features") + + +if __name__ == "__main__": + test_resize_with_bbox_op_voc_c(plot_vis=False) + test_resize_with_bbox_op_coco_c(plot_vis=False) + test_resize_with_bbox_op_edge_c(plot_vis=False) + test_resize_with_bbox_op_invalid_c() + test_resize_with_bbox_op_bad_c()