mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-27 02:20:31 +08:00
f450917ff5
* [lite] enable lite arm64-v8a fp16 option. * Update VERSION_NUMBER * [Vision] support custom labels for visualization * [Visualize] add custom labels warning * [Visualize] fix VisClassification bug
101 lines
3.1 KiB
C++
101 lines
3.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#ifdef ENABLE_VISION_VISUALIZE
|
|
|
|
#include <algorithm>
|
|
|
|
#include "fastdeploy/vision/visualize/visualize.h"
|
|
#include "opencv2/imgproc/imgproc.hpp"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
|
|
cv::Mat VisClassification(const cv::Mat& im, const ClassifyResult& result,
|
|
int top_k, float score_threshold, float font_size) {
|
|
int h = im.rows;
|
|
int w = im.cols;
|
|
auto vis_im = im.clone();
|
|
int h_sep = h / 30;
|
|
int w_sep = w / 10;
|
|
if (top_k > result.scores.size()) {
|
|
top_k = result.scores.size();
|
|
}
|
|
for (int i = 0; i < top_k; ++i) {
|
|
if (result.scores[i] < score_threshold) {
|
|
continue;
|
|
}
|
|
std::string id = std::to_string(result.label_ids[i]);
|
|
std::string score = std::to_string(result.scores[i]);
|
|
if (score.size() > 4) {
|
|
score = score.substr(0, 4);
|
|
}
|
|
std::string text = id + "," + score;
|
|
int font = cv::FONT_HERSHEY_SIMPLEX;
|
|
cv::Point origin;
|
|
origin.x = w_sep;
|
|
origin.y = h_sep * (i + 1);
|
|
cv::putText(vis_im, text, origin, font, font_size,
|
|
cv::Scalar(255, 255, 255), 1);
|
|
}
|
|
return vis_im;
|
|
}
|
|
|
|
// Visualize ClassifyResult with custom labels.
|
|
cv::Mat VisClassification(const cv::Mat& im, const ClassifyResult& result,
|
|
const std::vector<std::string>& labels,
|
|
int top_k, float score_threshold,
|
|
float font_size) {
|
|
int h = im.rows;
|
|
int w = im.cols;
|
|
auto vis_im = im.clone();
|
|
int h_sep = h / 30;
|
|
int w_sep = w / 10;
|
|
if (top_k > result.scores.size()) {
|
|
top_k = result.scores.size();
|
|
}
|
|
for (int i = 0; i < top_k; ++i) {
|
|
if (result.scores[i] < score_threshold) {
|
|
continue;
|
|
}
|
|
std::string id = std::to_string(result.label_ids[i]);
|
|
std::string score = std::to_string(result.scores[i]);
|
|
if (score.size() > 4) {
|
|
score = score.substr(0, 4);
|
|
}
|
|
std::string text = id + "," + score;
|
|
if (labels.size() > result.label_ids[i]) {
|
|
text = labels[result.label_ids[i]] + "," + text;
|
|
} else {
|
|
FDWARNING << "The label_id: " << result.label_ids[i]
|
|
<< " in DetectionResult should be less than length of labels:"
|
|
<< labels.size() << "." << std::endl;
|
|
}
|
|
if (text.size() > 16) {
|
|
text = text.substr(0, 16);
|
|
}
|
|
int font = cv::FONT_HERSHEY_SIMPLEX;
|
|
cv::Point origin;
|
|
origin.x = w_sep;
|
|
origin.y = h_sep * (i + 1);
|
|
cv::putText(vis_im, text, origin, font, font_size,
|
|
cv::Scalar(255, 255, 255), 1);
|
|
}
|
|
return vis_im;
|
|
}
|
|
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|
|
#endif
|