# Copyright (c) 2022 PaddlePaddle 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.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from paddlers_slim.models.ppdet.core.workspace import register
from paddlers_slim.models.ppdet.modeling.proposal_generator.target import label_box

__all__ = ['MaxIoUAssigner']


@register
class MaxIoUAssigner(object):
    """a standard bbox assigner based on max IoU, use ppdet's label_box
    as backend.
    Args:
        positive_overlap (float): threshold for defining positive samples
        negative_overlap (float): threshold for denining negative samples
        allow_low_quality (bool): whether to lower IoU thr if a GT poorly
            overlaps with candidate bboxes
    """

    def __init__(self,
                 positive_overlap,
                 negative_overlap,
                 allow_low_quality=True):
        self.positive_overlap = positive_overlap
        self.negative_overlap = negative_overlap
        self.allow_low_quality = allow_low_quality

    def __call__(self, bboxes, gt_bboxes):
        matches, match_labels = label_box(
            bboxes,
            gt_bboxes,
            positive_overlap=self.positive_overlap,
            negative_overlap=self.negative_overlap,
            allow_low_quality=self.allow_low_quality,
            ignore_thresh=-1,
            is_crowd=None,
            assign_on_cpu=False)
        return matches, match_labels