Files
FastDeploy/fastdeploy/vision/visualize/swap_background.cc
Jason 8ba4a26ebb Refine cpp/python api of visualize with lots of deprecated apis (#303)
* fix patchelf

* refine visualize api

* Update CMakeLists.txt

* refine visualize api

* add libs directory

* Create __init__.py
2022-09-29 14:06:45 +08:00

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