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a8458e6729
* Support new model PaddleSeg * Fix conflict * PaddleSeg add visulization function * fix bug * Fix BindPPSeg wrong name * Fix variable name * Update by comments * Add ppseg-unet example python version Co-authored-by: Jason <jiangjiajun@baidu.com>
99 lines
2.8 KiB
C++
99 lines
2.8 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/common/result.h"
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namespace fastdeploy {
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namespace vision {
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void ClassifyResult::Clear() {
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std::vector<int32_t>().swap(label_ids);
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std::vector<float>().swap(scores);
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}
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std::string ClassifyResult::Str() {
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std::string out;
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out = "ClassifyResult(\nlabel_ids: ";
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for (size_t i = 0; i < label_ids.size(); ++i) {
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out = out + std::to_string(label_ids[i]) + ", ";
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}
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out += "\nscores: ";
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for (size_t i = 0; i < label_ids.size(); ++i) {
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out = out + std::to_string(scores[i]) + ", ";
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}
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out += "\n)";
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return out;
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}
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DetectionResult::DetectionResult(const DetectionResult& res) {
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boxes.assign(res.boxes.begin(), res.boxes.end());
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scores.assign(res.scores.begin(), res.scores.end());
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label_ids.assign(res.label_ids.begin(), res.label_ids.end());
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}
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void DetectionResult::Clear() {
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std::vector<std::array<float, 4>>().swap(boxes);
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std::vector<float>().swap(scores);
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std::vector<int32_t>().swap(label_ids);
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}
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void DetectionResult::Reserve(int size) {
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boxes.reserve(size);
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scores.reserve(size);
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label_ids.reserve(size);
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}
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void DetectionResult::Resize(int size) {
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boxes.resize(size);
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scores.resize(size);
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label_ids.resize(size);
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}
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std::string DetectionResult::Str() {
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std::string out;
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out = "DetectionResult: [xmin, ymin, xmax, ymax, score, label_id]\n";
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for (size_t i = 0; i < boxes.size(); ++i) {
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out = out + std::to_string(boxes[i][0]) + "," +
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std::to_string(boxes[i][1]) + ", " + std::to_string(boxes[i][2]) +
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", " + std::to_string(boxes[i][3]) + ", " +
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std::to_string(scores[i]) + ", " + std::to_string(label_ids[i]) +
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"\n";
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}
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return out;
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}
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void SegmentationResult::Clear() {
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std::vector<std::vector<int64_t>>().swap(masks);
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}
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void SegmentationResult::Resize(int64_t height, int64_t width) {
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masks.resize(height, std::vector<int64_t>(width));
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}
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std::string SegmentationResult::Str() {
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std::string out;
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out = "SegmentationResult Image masks 10 rows x 10 cols: \n";
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for (size_t i = 0; i < 10; ++i) {
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out += "[";
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for (size_t j = 0; j < 10; ++j) {
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out = out + std::to_string(masks[i][j]) + ", ";
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}
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out += ".....]\n";
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}
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out += "...........\n";
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return out;
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}
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} // namespace vision
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} // namespace fastdeploy
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