mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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yeliang2258
a509dd8ec1
* add smoke model * add 3d vis * update code * update doc * mv paddle3d from detection to perception * update result for velocity * update code for CI * add set input data for TRT backend * add serving support for smoke model * update code * update code * update code --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
59 lines
2.2 KiB
C++
59 lines
2.2 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/perception/paddle3d/smoke/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 perception {
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SmokePostprocessor::SmokePostprocessor() {}
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bool SmokePostprocessor::Run(const std::vector<FDTensor>& tensors,
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std::vector<PerceptionResult>* results) {
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results->resize(1);
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(*results)[0].Clear();
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(*results)[0].Reserve(tensors[0].shape[0]);
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if (tensors[0].dtype != FDDataType::FP32) {
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FDERROR << "Only support post process with float32 data." << std::endl;
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return false;
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}
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const float* data = reinterpret_cast<const float*>(tensors[0].Data());
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auto result = &(*results)[0];
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for (int i = 0; i < tensors[0].shape[0] * tensors[0].shape[1]; i += 14) {
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// item 1 : class
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// item 2 : observation angle α
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// item 3 ~ 6 : box2d x1, y1, x2, y2
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// item 7 ~ 9 : box3d h, w, l
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// item 10 ~ 12 : box3d bottom center x, y, z
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// item 13 : box3d yaw angle
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// item 14 : score
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std::vector<float> vec(data + i, data + i + 14);
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result->scores.push_back(vec[13]);
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result->label_ids.push_back(vec[0]);
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result->boxes.emplace_back(std::array<float, 7>{
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vec[2], vec[3], vec[4], vec[5], vec[6], vec[7], vec[8]});
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result->center.emplace_back(std::array<float, 3>{vec[9], vec[10], vec[11]});
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result->observation_angle.push_back(vec[1]);
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result->yaw_angle.push_back(vec[12]);
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}
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return true;
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}
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} // namespace perception
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} // namespace vision
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} // namespace fastdeploy
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