Files
FastDeploy/csrcs/fastdeploy/vision/ppdet/build_preprocess.cc
2022-08-04 09:29:14 +00:00

87 lines
3.3 KiB
C++

// 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.
#include "fastdeploy/vision/common/processors/transform.h"
#include "fastdeploy/vision/ppdet/ppyoloe.h"
#include "yaml-cpp/yaml.h"
namespace fastdeploy {
namespace vision {
bool BuildPreprocessPipelineFromConfig(
std::vector<std::shared_ptr<Processor>>* processors,
const std::string& config_file) {
processors->clear();
YAML::Node cfg;
try {
cfg = YAML::LoadFile(config_file);
} catch (YAML::BadFile& e) {
FDERROR << "Failed to load yaml file " << config_file
<< ", maybe you should check this file." << std::endl;
return false;
}
processors->push_back(std::make_shared<BGR2RGB>());
for (const auto& op : cfg["Preprocess"]) {
std::string op_name = op["type"].as<std::string>();
if (op_name == "NormalizeImage") {
auto mean = op["mean"].as<std::vector<float>>();
auto std = op["std"].as<std::vector<float>>();
bool is_scale = op["is_scale"].as<bool>();
processors->push_back(std::make_shared<Normalize>(mean, std, is_scale));
} else if (op_name == "Resize") {
bool keep_ratio = op["keep_ratio"].as<bool>();
auto target_size = op["target_size"].as<std::vector<int>>();
int interp = op["interp"].as<int>();
FDASSERT(target_size.size(),
"Require size of target_size be 2, but now it's " +
std::to_string(target_size.size()) + ".");
if (!keep_ratio) {
int width = target_size[1];
int height = target_size[0];
processors->push_back(
std::make_shared<Resize>(width, height, -1.0, -1.0, interp, false));
} else {
int min_target_size = std::min(target_size[0], target_size[1]);
int max_target_size = std::max(target_size[0], target_size[1]);
processors->push_back(std::make_shared<ResizeByShort>(
min_target_size, interp, true, max_target_size));
}
} else if (op_name == "Permute") {
// Do nothing, do permute as the last operation
continue;
} else if (op_name == "Pad") {
auto size = op["size"].as<std::vector<int>>();
auto value = op["fill_value"].as<std::vector<float>>();
processors->push_back(std::make_shared<Cast>("float"));
processors->push_back(
std::make_shared<PadToSize>(size[1], size[0], value));
} else if (op_name == "PadStride") {
auto stride = op["stride"].as<int>();
processors->push_back(
std::make_shared<StridePad>(stride, std::vector<float>(3, 0)));
} else {
FDERROR << "Unexcepted preprocess operator: " << op_name << "."
<< std::endl;
return false;
}
}
processors->push_back(std::make_shared<HWC2CHW>());
return true;
}
} // namespace vision
} // namespace fastdeploy