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https://github.com/PaddlePaddle/FastDeploy.git
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* fix patchelf * refine visualize api * Update CMakeLists.txt * refine visualize api * add libs directory * Create __init__.py
225 lines
8.6 KiB
C++
225 lines
8.6 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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#ifdef ENABLE_VISION_VISUALIZE
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#include "fastdeploy/vision/visualize/visualize.h"
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#include "opencv2/highgui.hpp"
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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 SwapBackground(const cv::Mat& im, const cv::Mat& background,
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const MattingResult& result,
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bool remove_small_connected_area) {
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FDASSERT((!im.empty()), "Image can't be empty!");
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FDASSERT((im.channels() == 3), "Only support 3 channels image mat!");
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FDASSERT((!background.empty()), "Background image can't be empty!");
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FDASSERT((background.channels() == 3),
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"Only support 3 channels background image mat!");
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auto vis_img = im.clone();
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auto background_copy = background.clone();
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int out_h = static_cast<int>(result.shape[0]);
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int out_w = static_cast<int>(result.shape[1]);
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int height = im.rows;
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int width = im.cols;
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int bg_height = background.rows;
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int bg_width = background.cols;
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std::vector<float> alpha_copy;
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alpha_copy.assign(result.alpha.begin(), result.alpha.end());
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float* alpha_ptr = static_cast<float*>(alpha_copy.data());
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cv::Mat alpha(out_h, out_w, CV_32FC1, alpha_ptr);
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if (remove_small_connected_area) {
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alpha = Visualize::RemoveSmallConnectedArea(alpha, 0.05f);
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}
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if ((vis_img).type() != CV_8UC3) {
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(vis_img).convertTo((vis_img), CV_8UC3);
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}
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if ((background_copy).type() != CV_8UC3) {
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(background_copy).convertTo((background_copy), CV_8UC3);
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}
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if ((bg_height != height) || (bg_width != width)) {
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cv::resize(background, background_copy, cv::Size(width, height));
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}
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if ((out_h != height) || (out_w != width)) {
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cv::resize(alpha, alpha, cv::Size(width, height));
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}
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uchar* vis_data = static_cast<uchar*>(vis_img.data);
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uchar* background_data = static_cast<uchar*>(background_copy.data);
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uchar* im_data = static_cast<uchar*>(im.data);
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float* alpha_data = reinterpret_cast<float*>(alpha.data);
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for (size_t i = 0; i < height; ++i) {
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for (size_t j = 0; j < width; ++j) {
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float alpha_val = alpha_data[i * width + j];
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for (size_t c = 0; c < 3; ++c) {
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vis_data[i * width * 3 + j * 3 + c] = cv::saturate_cast<uchar>(
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static_cast<float>(im_data[i * width * 3 + j * 3 + c]) * alpha_val +
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(1.f - alpha_val) * background_data[i * width * 3 + j * 3 + c]);
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}
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}
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}
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return vis_img;
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}
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cv::Mat SwapBackground(const cv::Mat& im, const cv::Mat& background,
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const SegmentationResult& result, int background_label) {
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FDASSERT((!im.empty()), "Image can't be empty!");
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FDASSERT((im.channels() == 3), "Only support 3 channels image mat!");
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FDASSERT((!background.empty()), "Background image can't be empty!");
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FDASSERT((background.channels() == 3),
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"Only support 3 channels background image mat!");
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auto vis_img = im.clone();
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auto background_copy = background.clone();
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int height = im.rows;
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int width = im.cols;
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int bg_height = background.rows;
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int bg_width = background.cols;
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if ((vis_img).type() != CV_8UC3) {
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(vis_img).convertTo((vis_img), CV_8UC3);
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}
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if ((background_copy).type() != CV_8UC3) {
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(background_copy).convertTo((background_copy), CV_8UC3);
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}
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if ((bg_height != height) || (bg_width != width)) {
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cv::resize(background, background_copy, cv::Size(width, height));
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}
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uchar* vis_data = static_cast<uchar*>(vis_img.data);
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uchar* background_data = static_cast<uchar*>(background_copy.data);
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uchar* im_data = static_cast<uchar*>(im.data);
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float keep_value = 0.f;
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for (size_t i = 0; i < height; ++i) {
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for (size_t j = 0; j < width; ++j) {
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int category_id = result.label_map[i * width + j];
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if (background_label != category_id) {
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keep_value = 1.0f;
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} else {
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keep_value = 0.f;
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}
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for (size_t c = 0; c < 3; ++c) {
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vis_data[i * width * 3 + j * 3 + c] = cv::saturate_cast<uchar>(
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static_cast<float>(im_data[i * width * 3 + j * 3 + c]) *
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keep_value +
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(1.f - keep_value) * background_data[i * width * 3 + j * 3 + c]);
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}
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}
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}
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return vis_img;
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}
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cv::Mat Visualize::SwapBackgroundMatting(const cv::Mat& im,
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const cv::Mat& background,
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const MattingResult& result,
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bool remove_small_connected_area) {
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FDASSERT((!im.empty()), "Image can't be empty!");
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FDASSERT((im.channels() == 3), "Only support 3 channels image mat!");
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FDASSERT((!background.empty()), "Background image can't be empty!");
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FDASSERT((background.channels() == 3),
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"Only support 3 channels background image mat!");
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auto vis_img = im.clone();
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auto background_copy = background.clone();
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int out_h = static_cast<int>(result.shape[0]);
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int out_w = static_cast<int>(result.shape[1]);
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int height = im.rows;
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int width = im.cols;
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int bg_height = background.rows;
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int bg_width = background.cols;
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std::vector<float> alpha_copy;
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alpha_copy.assign(result.alpha.begin(), result.alpha.end());
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float* alpha_ptr = static_cast<float*>(alpha_copy.data());
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cv::Mat alpha(out_h, out_w, CV_32FC1, alpha_ptr);
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if (remove_small_connected_area) {
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alpha = Visualize::RemoveSmallConnectedArea(alpha, 0.05f);
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}
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if ((vis_img).type() != CV_8UC3) {
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(vis_img).convertTo((vis_img), CV_8UC3);
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}
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if ((background_copy).type() != CV_8UC3) {
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(background_copy).convertTo((background_copy), CV_8UC3);
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}
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if ((bg_height != height) || (bg_width != width)) {
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cv::resize(background, background_copy, cv::Size(width, height));
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}
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if ((out_h != height) || (out_w != width)) {
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cv::resize(alpha, alpha, cv::Size(width, height));
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}
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uchar* vis_data = static_cast<uchar*>(vis_img.data);
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uchar* background_data = static_cast<uchar*>(background_copy.data);
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uchar* im_data = static_cast<uchar*>(im.data);
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float* alpha_data = reinterpret_cast<float*>(alpha.data);
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for (size_t i = 0; i < height; ++i) {
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for (size_t j = 0; j < width; ++j) {
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float alpha_val = alpha_data[i * width + j];
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for (size_t c = 0; c < 3; ++c) {
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vis_data[i * width * 3 + j * 3 + c] = cv::saturate_cast<uchar>(
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static_cast<float>(im_data[i * width * 3 + j * 3 + c]) * alpha_val +
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(1.f - alpha_val) * background_data[i * width * 3 + j * 3 + c]);
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}
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}
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}
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return vis_img;
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}
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cv::Mat Visualize::SwapBackgroundSegmentation(
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const cv::Mat& im, const cv::Mat& background, int background_label,
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const SegmentationResult& result) {
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FDASSERT((!im.empty()), "Image can't be empty!");
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FDASSERT((im.channels() == 3), "Only support 3 channels image mat!");
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FDASSERT((!background.empty()), "Background image can't be empty!");
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FDASSERT((background.channels() == 3),
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"Only support 3 channels background image mat!");
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auto vis_img = im.clone();
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auto background_copy = background.clone();
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int height = im.rows;
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int width = im.cols;
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int bg_height = background.rows;
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int bg_width = background.cols;
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if ((vis_img).type() != CV_8UC3) {
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(vis_img).convertTo((vis_img), CV_8UC3);
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}
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if ((background_copy).type() != CV_8UC3) {
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(background_copy).convertTo((background_copy), CV_8UC3);
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}
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if ((bg_height != height) || (bg_width != width)) {
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cv::resize(background, background_copy, cv::Size(width, height));
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}
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uchar* vis_data = static_cast<uchar*>(vis_img.data);
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uchar* background_data = static_cast<uchar*>(background_copy.data);
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uchar* im_data = static_cast<uchar*>(im.data);
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float keep_value = 0.f;
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for (size_t i = 0; i < height; ++i) {
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for (size_t j = 0; j < width; ++j) {
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int category_id = result.label_map[i * width + j];
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if (background_label != category_id) {
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keep_value = 1.0f;
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} else {
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keep_value = 0.f;
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}
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for (size_t c = 0; c < 3; ++c) {
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vis_data[i * width * 3 + j * 3 + c] = cv::saturate_cast<uchar>(
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static_cast<float>(im_data[i * width * 3 + j * 3 + c]) *
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keep_value +
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(1.f - keep_value) * background_data[i * width * 3 + j * 3 + c]);
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}
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}
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}
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return vis_img;
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}
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} // namespace vision
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} // namespace fastdeploy
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#endif
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