"""
Copyright 2020 The OneFlow 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 random

import numpy as np
import oneflow as flow
import oneflow.typing as oft


def _of_object_segm_poly_flip(poly_list, image_size, flip_code):
    poly_shape = _get_segm_poly_static_shape(poly_list)

    flow.clear_default_session()
    func_config = flow.FunctionConfig()
    func_config.default_data_type(flow.float)
    func_config.default_logical_view(flow.scope.mirrored_view())

    @flow.global_function(function_config=func_config)
    def object_segm_poly_flip_job(
        poly_def: oft.ListListNumpy.Placeholder(
            shape=tuple(poly_shape), dtype=flow.float
        ),
        image_size_def: oft.ListNumpy.Placeholder(
            shape=image_size.shape, dtype=flow.int32
        ),
    ):
        poly_buffer = flow.tensor_list_to_tensor_buffer(poly_def)
        flip_poly = flow.object_segmentation_polygon_flip(
            poly_buffer, image_size_def, flip_code
        )
        return flow.tensor_buffer_to_tensor_list(
            flip_poly, shape=poly_shape[1:], dtype=flow.float
        )

    input_poly_list = [np.expand_dims(bbox, axis=0) for bbox in poly_list]
    poly_tensor = object_segm_poly_flip_job([input_poly_list], [image_size]).get()
    return poly_tensor.numpy_lists()[0]


def _get_segm_poly_static_shape(poly_list):
    poly_shapes = [poly.shape for poly in poly_list]
    poly_static_shape = np.amax(poly_shapes, axis=0)
    assert isinstance(
        poly_static_shape, np.ndarray
    ), "poly_shapes: {}, poly_static_shape: {}".format(
        str(poly_shapes), str(poly_static_shape)
    )
    poly_static_shape = poly_static_shape.tolist()
    poly_static_shape.insert(0, len(poly_list))
    return poly_static_shape


def _compare_segm_poly_flip(
    test_case, anno_file, batch_size, flip_code, print_debug_info=False
):
    from pycocotools.coco import COCO

    coco = COCO(anno_file)
    img_ids = coco.getImgIds()

    segm_poly_list = []
    image_size_list = []
    sample_cnt = 0
    while sample_cnt < batch_size:
        rand_img_id = random.choice(img_ids)
        anno_ids = coco.getAnnIds(imgIds=[rand_img_id])
        if len(anno_ids) == 0:
            continue

        poly_pts = []
        for anno_id in anno_ids:
            anno = coco.anns[anno_id]
            if anno["iscrowd"] != 0:
                continue
            assert isinstance(anno["segmentation"], list)
            for poly in anno["segmentation"]:
                assert isinstance(poly, list)
                poly_pts.extend(poly)

        poly_array = np.array(poly_pts, dtype=np.single).reshape(-1, 2)
        segm_poly_list.append(poly_array)
        image_size_list.append(
            [coco.imgs[rand_img_id]["width"], coco.imgs[rand_img_id]["height"]]
        )
        sample_cnt += 1

    image_size_array = np.array(image_size_list, dtype=np.int32)
    of_segm_poly_list = _of_object_segm_poly_flip(
        segm_poly_list, image_size_array, flip_code
    )
    for of_poly, poly, image_size in zip(
        of_segm_poly_list, segm_poly_list, image_size_list
    ):
        w, h = image_size
        if flip_code == 1:
            poly[:, 0] = w - poly[:, 0]
        else:
            raise NotImplementedError

        if print_debug_info:
            print("-" * 20)
            print("of_poly:", of_poly.squeeze().shape, "\n", of_poly.squeeze())
            print("poly:", poly.shape, "\n", poly)

    test_case.assertTrue(np.allclose(of_poly.squeeze(), poly))


# @flow.unittest.skip_unless_1n1d()
# TODO(zhangwenxiao, jiangxuefei): refine in multi-client
@unittest.skipIf(True, "skip for now because of single-client tensor_list removed")
class TestObjectSegmPolyFlip(flow.unittest.TestCase):
    def test_object_segm_poly_flip(test_case):
        _compare_segm_poly_flip(
            test_case, "/dataset/mscoco_2017/annotations/instances_val2017.json", 4, 1
        )


if __name__ == "__main__":
    unittest.main()
