You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
110 lines
3.7 KiB
110 lines
3.7 KiB
# 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 |
|
|
|
import paddle |
|
|
|
from paddlers_slim.models.ppdet.core.workspace import register, create |
|
from .meta_arch import BaseArch |
|
|
|
__all__ = ['SOLOv2'] |
|
|
|
|
|
@register |
|
class SOLOv2(BaseArch): |
|
""" |
|
SOLOv2 network, see https://arxiv.org/abs/2003.10152 |
|
|
|
Args: |
|
backbone (object): an backbone instance |
|
solov2_head (object): an `SOLOv2Head` instance |
|
mask_head (object): an `SOLOv2MaskHead` instance |
|
neck (object): neck of network, such as feature pyramid network instance |
|
""" |
|
|
|
__category__ = 'architecture' |
|
|
|
def __init__(self, backbone, solov2_head, mask_head, neck=None): |
|
super(SOLOv2, self).__init__() |
|
self.backbone = backbone |
|
self.neck = neck |
|
self.solov2_head = solov2_head |
|
self.mask_head = mask_head |
|
|
|
@classmethod |
|
def from_config(cls, cfg, *args, **kwargs): |
|
backbone = create(cfg['backbone']) |
|
|
|
kwargs = {'input_shape': backbone.out_shape} |
|
neck = create(cfg['neck'], **kwargs) |
|
|
|
kwargs = {'input_shape': neck.out_shape} |
|
solov2_head = create(cfg['solov2_head'], **kwargs) |
|
mask_head = create(cfg['mask_head'], **kwargs) |
|
|
|
return { |
|
'backbone': backbone, |
|
'neck': neck, |
|
'solov2_head': solov2_head, |
|
'mask_head': mask_head, |
|
} |
|
|
|
def model_arch(self): |
|
body_feats = self.backbone(self.inputs) |
|
|
|
body_feats = self.neck(body_feats) |
|
|
|
self.seg_pred = self.mask_head(body_feats) |
|
|
|
self.cate_pred_list, self.kernel_pred_list = self.solov2_head( |
|
body_feats) |
|
|
|
def get_loss(self, ): |
|
loss = {} |
|
# get gt_ins_labels, gt_cate_labels, etc. |
|
gt_ins_labels, gt_cate_labels, gt_grid_orders = [], [], [] |
|
fg_num = self.inputs['fg_num'] |
|
for i in range(len(self.solov2_head.seg_num_grids)): |
|
ins_label = 'ins_label{}'.format(i) |
|
if ins_label in self.inputs: |
|
gt_ins_labels.append(self.inputs[ins_label]) |
|
cate_label = 'cate_label{}'.format(i) |
|
if cate_label in self.inputs: |
|
gt_cate_labels.append(self.inputs[cate_label]) |
|
grid_order = 'grid_order{}'.format(i) |
|
if grid_order in self.inputs: |
|
gt_grid_orders.append(self.inputs[grid_order]) |
|
|
|
loss_solov2 = self.solov2_head.get_loss( |
|
self.cate_pred_list, self.kernel_pred_list, self.seg_pred, |
|
gt_ins_labels, gt_cate_labels, gt_grid_orders, fg_num) |
|
loss.update(loss_solov2) |
|
total_loss = paddle.add_n(list(loss.values())) |
|
loss.update({'loss': total_loss}) |
|
return loss |
|
|
|
def get_pred(self): |
|
seg_masks, cate_labels, cate_scores, bbox_num = self.solov2_head.get_prediction( |
|
self.cate_pred_list, self.kernel_pred_list, self.seg_pred, |
|
self.inputs['im_shape'], self.inputs['scale_factor']) |
|
outs = { |
|
"segm": seg_masks, |
|
"bbox_num": bbox_num, |
|
'cate_label': cate_labels, |
|
'cate_score': cate_scores |
|
} |
|
return outs
|
|
|