mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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df20b2a02b
* Remove useless macros * triger ci * fix check error * rename INTEGRATE_PADDLE2ONNX to ENABLE_PADDLE2ONNX
97 lines
3.1 KiB
C++
97 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 <algorithm>
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#include "fastdeploy/vision/visualize/visualize.h"
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#include "opencv2/imgproc/imgproc.hpp"
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namespace fastdeploy {
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namespace vision {
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cv::Mat VisClassification(const cv::Mat& im, const ClassifyResult& result,
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int top_k, float score_threshold, float font_size) {
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int h = im.rows;
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int w = im.cols;
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auto vis_im = im.clone();
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int h_sep = h / 30;
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int w_sep = w / 10;
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if (top_k > result.scores.size()) {
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top_k = result.scores.size();
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}
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for (int i = 0; i < top_k; ++i) {
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if (result.scores[i] < score_threshold) {
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continue;
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}
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std::string id = std::to_string(result.label_ids[i]);
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std::string score = std::to_string(result.scores[i]);
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if (score.size() > 4) {
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score = score.substr(0, 4);
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}
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std::string text = id + "," + score;
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int font = cv::FONT_HERSHEY_SIMPLEX;
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cv::Point origin;
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origin.x = w_sep;
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origin.y = h_sep * (i + 1);
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cv::putText(vis_im, text, origin, font, font_size,
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cv::Scalar(255, 255, 255), 1);
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}
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return vis_im;
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}
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// Visualize ClassifyResult with custom labels.
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cv::Mat VisClassification(const cv::Mat& im, const ClassifyResult& result,
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const std::vector<std::string>& labels, int top_k,
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float score_threshold, float font_size) {
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int h = im.rows;
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int w = im.cols;
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auto vis_im = im.clone();
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int h_sep = h / 30;
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int w_sep = w / 10;
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if (top_k > result.scores.size()) {
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top_k = result.scores.size();
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}
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for (int i = 0; i < top_k; ++i) {
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if (result.scores[i] < score_threshold) {
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continue;
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}
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std::string id = std::to_string(result.label_ids[i]);
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std::string score = std::to_string(result.scores[i]);
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if (score.size() > 4) {
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score = score.substr(0, 4);
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}
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std::string text = id + "," + score;
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if (labels.size() > result.label_ids[i]) {
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text = labels[result.label_ids[i]] + "," + text;
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} else {
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FDWARNING << "The label_id: " << result.label_ids[i]
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<< " in DetectionResult should be less than length of labels:"
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<< labels.size() << "." << std::endl;
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}
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if (text.size() > 16) {
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text = text.substr(0, 16);
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}
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int font = cv::FONT_HERSHEY_SIMPLEX;
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cv::Point origin;
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origin.x = w_sep;
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origin.y = h_sep * (i + 1);
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cv::putText(vis_im, text, origin, font, font_size,
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cv::Scalar(255, 255, 255), 1);
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}
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return vis_im;
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}
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} // namespace vision
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} // namespace fastdeploy
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