# Copyright 2021 biubug6 . 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.
# This code is modified by Zilliz.
#adapted from https://github.com/biubug6/Pytorch_Retinaface
import torch
import torch.nn.functional as F
from torch import nn
from towhee.models.retina_face.utils import conv_bn, conv_bn_no_relu
[docs]class SSH(nn.Module):
"""
SSH Module
Single stage headless Module inspired by SSH: Single Stage Headless Face Detector.
Described in: https://arxiv.org/abs/1708.03979.
Args:
in_channel (`int`):
number of input channels.
out_channel (`int`):
number of output channels.
"""
[docs] def __init__(self, in_channel: int, out_channel: int):
super().__init__()
assert out_channel % 4 == 0
leaky = 0
if out_channel <= 64:
leaky = 0.1
self.conv3x3 = conv_bn_no_relu(in_channel, out_channel//2, stride=1)
self.conv5x5_1 = conv_bn(in_channel, out_channel//4, stride=1, leaky = leaky)
self.conv5x5_2 = conv_bn_no_relu(out_channel//4, out_channel//4, stride=1)
self.conv7x7_2 = conv_bn(out_channel//4, out_channel//4, stride=1, leaky = leaky)
self.conv7x7_3 = conv_bn_no_relu(out_channel//4, out_channel//4, stride=1)
[docs] def forward(self, x: torch.FloatTensor):
conv3x3 = self.conv3x3(x)
conv5x5_1 = self.conv5x5_1(x)
conv5x5 = self.conv5x5_2(conv5x5_1)
conv7x7_2 = self.conv7x7_2(conv5x5_1)
conv7x7 = self.conv7x7_3(conv7x7_2)
out = torch.cat([conv3x3, conv5x5, conv7x7], dim=1)
out = F.relu(out)
return out
