Files
FastDeploy/fastdeploy/vision/classification/ppcls/postprocessor.cc
Jason 3589c0fa94 [Model] Refactor PaddleClas module (#505)
* Refactor the PaddleClas module

* fix bug

* remove debug code

* clean unused code

* support pybind

* Update fd_tensor.h

* Update fd_tensor.cc

* temporary revert python api

* fix ci error

* fix code style problem
2022-11-07 19:33:47 +08:00

54 lines
1.8 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/classification/ppcls/postprocessor.h"
#include "fastdeploy/vision/utils/utils.h"
namespace fastdeploy {
namespace vision {
namespace classification {
PaddleClasPostprocessor::PaddleClasPostprocessor(int topk) {
topk_ = topk;
initialized_ = true;
}
bool PaddleClasPostprocessor::Run(const std::vector<FDTensor>& infer_result, std::vector<ClassifyResult>* results) {
if (!initialized_) {
FDERROR << "Postprocessor is not initialized." << std::endl;
return false;
}
int batch = infer_result[0].shape[0];
int num_classes = infer_result[0].shape[1];
const float* infer_result_data = reinterpret_cast<const float*>(infer_result[0].Data());
results->resize(batch);
int topk = std::min(num_classes, topk_);
for (int i = 0; i < batch; ++i) {
(*results)[i].label_ids = utils::TopKIndices(infer_result_data + i * num_classes, num_classes, topk);
(*results)[i].scores.resize(topk);
for (int j = 0; j < topk; ++j) {
(*results)[i].scores[j] = infer_result_data[i * num_classes + (*results)[i].label_ids[j]];
}
}
return true;
}
} // namespace classification
} // namespace vision
} // namespace fastdeploy