updating ut for RandomHorizontalFlipWithBBox and BBoxAugment

tests/ut/python/dataset/test_random_horizontal_flip_with_bbox.py

@@ -0,0 +1,229 @@
+# 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 horizontal flip with bounding boxes op in DE
+"""
+import numpy as np
+import mindspore.log as logger
+import mindspore.dataset as ds
+import mindspore.dataset.transforms.vision.c_transforms as c_vision
+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"
+
+
+def fix_annotate(bboxes):
+    """
+    Fix annotations to format followed by mindspore.
+    :param bboxes: in [label, x_min, y_min, w, h, truncate, difficult] format
+    :return: annotation in [x_min, y_min, w, h, label, truncate, difficult] format
+    """
+    for bbox in bboxes:
+        tmp = bbox[0]
+        bbox[0] = bbox[1]
+        bbox[1] = bbox[2]
+        bbox[2] = bbox[3]
+        bbox[3] = bbox[4]
+        bbox[4] = tmp
+    return bboxes
+
+
+def test_random_horizontal_flip_with_bbox_op_c(plot_vis=False):
+    """
+    Prints images side by side with and without Aug applied + bboxes to
+    compare and test
+    """
+    logger.info("test_random_horizontal_flip_with_bbox_op_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.RandomHorizontalFlipWithBBox(1)
+
+    # maps to fix annotations to minddata standard
+    dataVoc1 = dataVoc1.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    dataVoc2 = dataVoc2.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    # map to apply ops
+    dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                            output_columns=["image", "annotation"],
+                            columns_order=["image", "annotation"],
+                            operations=[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_horizontal_bbox_with_bbox_valid_rand_c(plot_vis=False):
+    """
+    Uses a valid non-default input, expect to pass
+    Prints images side by side with and without Aug applied + bboxes to
+    compare and test
+    """
+    logger.info("test_random_horizontal_bbox_valid_rand_c")
+
+    original_seed = config_get_set_seed(1)
+    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.RandomHorizontalFlipWithBBox(0.6)
+
+    # maps to fix annotations to minddata standard
+    dataVoc1 = dataVoc1.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    dataVoc2 = dataVoc2.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    # map to apply ops
+    dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                            output_columns=["image", "annotation"],
+                            columns_order=["image", "annotation"],
+                            operations=[test_op])
+
+    filename = "random_horizontal_flip_with_bbox_01_c_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_horizontal_flip_with_bbox_valid_edge_c(plot_vis=False):
+    """
+    Test RandomHorizontalFlipWithBBox op (testing with valid edge case, box covering full image).
+    Prints images side by side with and without Aug applied + bboxes to compare and test
+    """
+    logger.info("test_horizontal_flip_with_bbox_valid_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.RandomHorizontalFlipWithBBox(1)
+
+    # maps to fix annotations to minddata standard
+    dataVoc1 = dataVoc1.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    dataVoc2 = dataVoc2.map(input_columns=["annotation"],
+                            output_columns=["annotation"],
+                            operations=fix_annotate)
+    # map to apply ops
+    # Add column for "annotation"
+    dataVoc1 = dataVoc1.map(input_columns=["image", "annotation"],
+                            output_columns=["image", "annotation"],
+                            columns_order=["image", "annotation"],
+                            operations=lambda img, bbox:
+                            (img, np.array([[0, 0, img.shape[1], img.shape[0], 0, 0, 0]]).astype(np.uint32)))
+    dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                            output_columns=["image", "annotation"],
+                            columns_order=["image", "annotation"],
+                            operations=lambda img, bbox:
+                            (img, np.array([[0, 0, img.shape[1], img.shape[0], 0, 0, 0]]).astype(np.uint32)))
+    dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                            output_columns=["image", "annotation"],
+                            columns_order=["image", "annotation"],
+                            operations=[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_horizontal_flip_with_bbox_invalid_prob_c():
+    """
+    Test RandomHorizontalFlipWithBBox op with invalid input probability
+    """
+    logger.info("test_random_horizontal_bbox_invalid_prob_c")
+
+    dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False)
+
+    try:
+        # Note: Valid range of prob should be [0.0, 1.0]
+        test_op = c_vision.RandomHorizontalFlipWithBBox(1.5)
+        dataVoc2 = dataVoc2.map(input_columns=["annotation"],
+                                output_columns=["annotation"],
+                                operations=fix_annotate)
+        # map to apply ops
+        dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                                output_columns=["image", "annotation"],
+                                columns_order=["image", "annotation"],
+                                operations=[test_op])  # Add column for "annotation"
+    except ValueError as error:
+        logger.info("Got an exception in DE: {}".format(str(error)))
+        assert "Input is not" in str(error)
+
+
+def test_random_horizontal_flip_with_bbox_invalid_bounds_c():
+    """
+    Test RandomHorizontalFlipWithBBox op with invalid bounding boxes
+    """
+    logger.info("test_random_horizontal_bbox_invalid_bounds_c")
+
+    test_op = c_vision.RandomHorizontalFlipWithBBox(1)
+
+    dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False)
+    check_bad_bbox(dataVoc2, test_op, InvalidBBoxType.WidthOverflow, "bounding boxes is out of bounds of the image")
+    dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False)
+    check_bad_bbox(dataVoc2, test_op, InvalidBBoxType.HeightOverflow, "bounding boxes is out of bounds of the image")
+    dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False)
+    check_bad_bbox(dataVoc2, test_op, InvalidBBoxType.NegativeXY, "min_x")
+    dataVoc2 = ds.VOCDataset(DATA_DIR, task="Detection", mode="train", decode=True, shuffle=False)
+    check_bad_bbox(dataVoc2, test_op, InvalidBBoxType.WrongShape, "4 features")
+
+
+if __name__ == "__main__":
+    # set to false to not show plots
+    test_random_horizontal_flip_with_bbox_op_c(plot_vis=False)
+    test_random_horizontal_bbox_with_bbox_valid_rand_c(plot_vis=False)
+    test_random_horizontal_flip_with_bbox_valid_edge_c(plot_vis=False)
+    test_random_horizontal_flip_with_bbox_invalid_prob_c()
+    test_random_horizontal_flip_with_bbox_invalid_bounds_c()