mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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86 lines
3.1 KiB
C++
86 lines
3.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "fastdeploy/vision/ocr/ppocr/cls_postprocessor.h"
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#include "fastdeploy/utils/perf.h"
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#include "fastdeploy/vision/ocr/ppocr/utils/ocr_utils.h"
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namespace fastdeploy {
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namespace vision {
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namespace ocr {
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bool SingleBatchPostprocessor(const float* out_data, const size_t& length,
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int* cls_label, float* cls_score) {
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*cls_label = std::distance(&out_data[0],
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std::max_element(&out_data[0], &out_data[length]));
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*cls_score = float(*std::max_element(&out_data[0], &out_data[length]));
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return true;
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}
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bool ClassifierPostprocessor::Run(const std::vector<FDTensor>& tensors,
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std::vector<int32_t>* cls_labels,
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std::vector<float>* cls_scores) {
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size_t total_size = tensors[0].shape[0];
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return Run(tensors, cls_labels, cls_scores, 0, total_size);
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}
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bool ClassifierPostprocessor::Run(const std::vector<FDTensor>& tensors,
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std::vector<int32_t>* cls_labels,
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std::vector<float>* cls_scores,
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size_t start_index, size_t total_size) {
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// Classifier have only 1 output tensor.
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const FDTensor& tensor = tensors[0];
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// For Classifier, the output tensor shape = [batch,2]
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size_t batch = tensor.shape[0];
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size_t length = accumulate(tensor.shape.begin() + 1, tensor.shape.end(), 1,
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std::multiplies<int>());
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if (batch <= 0) {
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FDERROR << "The infer outputTensor.shape[0] <=0, wrong infer result."
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<< std::endl;
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return false;
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}
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if (start_index < 0 || total_size <= 0) {
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FDERROR << "start_index or total_size error. Correct is: 0 <= start_index "
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"< total_size"
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<< std::endl;
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return false;
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}
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if ((start_index + batch) > total_size) {
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FDERROR << "start_index or total_size error. Correct is: start_index + "
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"batch(outputTensor.shape[0]) <= total_size"
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<< std::endl;
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return false;
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}
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cls_labels->resize(total_size);
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cls_scores->resize(total_size);
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const float* tensor_data = reinterpret_cast<const float*>(tensor.Data());
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for (int i_batch = 0; i_batch < batch; ++i_batch) {
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SingleBatchPostprocessor(tensor_data+ i_batch * length,
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length,
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&cls_labels->at(i_batch + start_index),
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&cls_scores->at(i_batch + start_index));
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}
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return true;
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}
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} // namespace ocr
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} // namespace vision
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} // namespace fastdeploy
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