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9cd00ad4c5
* Refactoring code of YOLOv5Cls with new model type * fix reviewed problem * Normalize&HWC2CHW -> NormalizeAndPermute * remove cast()
59 lines
2.0 KiB
C++
59 lines
2.0 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/classification/contrib/yolov5cls/postprocessor.h"
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#include "fastdeploy/vision/utils/utils.h"
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namespace fastdeploy {
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namespace vision {
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namespace classification {
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YOLOv5ClsPostprocessor::YOLOv5ClsPostprocessor() {
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topk_ = 1;
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}
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bool YOLOv5ClsPostprocessor::Run(
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const std::vector<FDTensor> &tensors, std::vector<ClassifyResult> *results,
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const std::vector<std::map<std::string, std::array<float, 2>>> &ims_info) {
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int batch = tensors[0].shape[0];
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FDTensor infer_result = tensors[0];
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FDTensor infer_result_softmax;
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function::Softmax(infer_result, &infer_result_softmax, 1);
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results->resize(batch);
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for (size_t bs = 0; bs < batch; ++bs) {
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(*results)[bs].Clear();
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// output (1,1000) score classnum 1000
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int num_classes = infer_result_softmax.shape[1];
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const float* infer_result_buffer =
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reinterpret_cast<const float*>(infer_result_softmax.Data()) + bs * infer_result_softmax.shape[1];
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topk_ = std::min(num_classes, topk_);
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(*results)[bs].label_ids =
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utils::TopKIndices(infer_result_buffer, num_classes, topk_);
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(*results)[bs].scores.resize(topk_);
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for (int i = 0; i < topk_; ++i) {
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(*results)[bs].scores[i] = *(infer_result_buffer + (*results)[bs].label_ids[i]);
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}
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if ((*results)[bs].label_ids.size() == 0) {
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return true;
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}
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}
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return true;
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}
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} // namespace classification
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} // namespace vision
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} // namespace fastdeploy
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