wt_ocr_and_docker/ppocr/modeling/heads/det_pse_head.py

# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# 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 refer from:
https://github.com/whai362/PSENet/blob/python3/models/head/psenet_head.py
"""

from paddle import nn


class PSEHead(nn.Layer):
    def __init__(self, in_channels, hidden_dim=256, out_channels=7, **kwargs):
        super(PSEHead, self).__init__()
        self.conv1 = nn.Conv2D(
            in_channels, hidden_dim, kernel_size=3, stride=1, padding=1)
        self.bn1 = nn.BatchNorm2D(hidden_dim)
        self.relu1 = nn.ReLU()

        self.conv2 = nn.Conv2D(
            hidden_dim, out_channels, kernel_size=1, stride=1, padding=0)

    def forward(self, x, **kwargs):
        out = self.conv1(x)
        out = self.relu1(self.bn1(out))
        out = self.conv2(out)
        return {'maps': out}