# Copyright 2020-2022 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
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# ==============================================================================
"""
Testing the random horizontal flip with bounding boxes op in DE
"""
import mindspore.log as logger
import mindspore.dataset as ds
import mindspore.dataset.vision as vision
from util import InvalidBBoxType, check_bad_bbox, \
    config_get_set_seed, config_get_set_num_parallel_workers, save_and_check_md5, \
    helper_perform_ops_bbox, helper_test_visual_bbox, helper_perform_ops_bbox_edgecase_float

GENERATE_GOLDEN = False

# updated VOC dataset with correct annotations
DATA_DIR = "../data/dataset/testVOC2012_2"
DATA_DIR_2 = ["../data/dataset/testCOCO/train/",
              "../data/dataset/testCOCO/annotations/train.json"]  # DATA_DIR, ANNOTATION_DIR


def METHOD_NAME(plot_vis=False):
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description: Prints images and bboxes side by side with and without RandomHorizontalFlipWithBBox Op applied
    Expectation: Prints images and bboxes side by side
    """
    logger.info("test_random_horizontal_flip_with_bbox_op_c")

    # Load dataset
    data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    test_op = vision.RandomHorizontalFlipWithBBox(1)

    data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)

    helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)


def test_random_horizontal_flip_with_bbox_op_coco_c(plot_vis=False):
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description: Prints images and bboxes side by side with and without the Op applied using CocoDataset
    Expectation: Prints images and bboxes side by side
    """
    logger.info("test_random_horizontal_flip_with_bbox_op_coco_c")

    data_coco1 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection",
                                decode=True, shuffle=False)

    data_coco2 = ds.CocoDataset(DATA_DIR_2[0], annotation_file=DATA_DIR_2[1], task="Detection",
                                decode=True, shuffle=False)

    test_op = vision.RandomHorizontalFlipWithBBox(1)

    data_coco2 = helper_perform_ops_bbox(data_coco2, test_op)

    helper_test_visual_bbox(plot_vis, data_coco1, data_coco2)


def test_random_horizontal_flip_with_bbox_valid_rand_c(plot_vis=False):
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description: Prints images and bboxes side by side with and without aug and the Op applied valid non-default input
    Expectation: Passes the comparison 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
    data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    test_op = vision.RandomHorizontalFlipWithBBox(0.6)

    # map to apply ops
    data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
    data_voc2 = data_voc2.project(["image", "bbox"])

    filename = "random_horizontal_flip_with_bbox_01_c_result.npz"
    save_and_check_md5(data_voc2, filename, generate_golden=GENERATE_GOLDEN)

    helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)

    # 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):
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description: Prints images side by side with and without aug applied and the Op to compare and test on edge case
    Expectation: Passes the edge case, box covering full image
    """
    logger.info("test_horizontal_flip_with_bbox_valid_edge_c")

    data_voc1 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)
    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    test_op = vision.RandomHorizontalFlipWithBBox(1)

    # map to apply ops
    data_voc1 = helper_perform_ops_bbox_edgecase_float(data_voc1)
    data_voc2 = helper_perform_ops_bbox_edgecase_float(data_voc2)
    data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)

    helper_test_visual_bbox(plot_vis, data_voc1, data_voc2)


def test_random_horizontal_flip_with_bbox_invalid_prob_c():
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description:test RandomHorizonFlipWithBBox op with invalid input probability
    Expectation: Error is raised as expected
    """
    logger.info("test_random_horizontal_bbox_invalid_prob_c")

    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)

    try:
        # Note: Valid range of prob should be [0.0, 1.0]
        test_op = vision.RandomHorizontalFlipWithBBox(1.5)
        # map to apply ops
        data_voc2 = helper_perform_ops_bbox(data_voc2, test_op)
    except ValueError as error:
        logger.info("Got an exception in DE: {}".format(str(error)))
        assert "Input prob is not within the required interval of [0.0, 1.0]." in str(
            error)


def test_random_horizontal_flip_with_bbox_invalid_bounds_c():
    """
    Feature: RandomHorizontalFlipWithBBox op
    Description: Test RandomHorizontalFlipWithBBox op with invalid bounding boxes
    Expectation: Correct error is thrown as expected
    """
    logger.info("test_random_horizontal_bbox_invalid_bounds_c")

    test_op = vision.RandomHorizontalFlipWithBBox(1)

    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)
    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",
                              usage="train", shuffle=False, decode=True)
    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",
                              usage="train", shuffle=False, decode=True)
    check_bad_bbox(data_voc2, test_op,
                   InvalidBBoxType.NegativeXY, "negative value")
    data_voc2 = ds.VOCDataset(DATA_DIR, task="Detection",
                              usage="train", shuffle=False, decode=True)
    check_bad_bbox(data_voc2, test_op,
                   InvalidBBoxType.WrongShape, "4 features")


if __name__ == "__main__":
    # set to false to not show plots
    METHOD_NAME(plot_vis=False)
    test_random_horizontal_flip_with_bbox_op_coco_c(plot_vis=False)
    test_random_horizontal_flip_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()