49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import paddle
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import paddle.nn.functional as F
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from ppdet.core.workspace import register, serializable
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from .iou_loss import IouLoss
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from ..bbox_utils import xywh2xyxy, bbox_iou
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@register
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@serializable
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class IouAwareLoss(IouLoss):
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"""
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iou aware loss, see https://arxiv.org/abs/1912.05992
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Args:
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loss_weight (float): iou aware loss weight, default is 1.0
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max_height (int): max height of input to support random shape input
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max_width (int): max width of input to support random shape input
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"""
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def __init__(self, loss_weight=1.0, giou=False, diou=False, ciou=False):
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super(IouAwareLoss, self).__init__(
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loss_weight=loss_weight, giou=giou, diou=diou, ciou=ciou)
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def __call__(self, ioup, pbox, gbox):
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iou = bbox_iou(
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pbox, gbox, giou=self.giou, diou=self.diou, ciou=self.ciou)
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iou.stop_gradient = True
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loss_iou_aware = F.binary_cross_entropy_with_logits(
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ioup, iou, reduction='none')
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loss_iou_aware = loss_iou_aware * self.loss_weight
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return loss_iou_aware
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