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FIX:upgrade cluster algorithm to remove duplicate labels 

jira: none
Change-Id: I4d68d8cd8e080932c7c308bc8f69e27546ffe309
This commit is contained in:
zhou.xu 2024-05-09 14:06:59 +08:00 committed by Lane.Wei
parent 86d345eee8
commit 7fcf5aaaf1
1 changed files with 90 additions and 19 deletions
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109
src/libslic3r/ObjColorUtils.hpp
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@ -27,7 +27,8 @@ public:
cv::Mat image8UC3;
convert_color_space(flatten_image8UC3, image8UC3, color_space);
cv::Mat image32FC3(image8UC3.rows, 1, CV_32FC3);
for (int i = 0; i < image8UC3.rows; i++) image32FC3.at<cv::Vec3f>(i, 0) = image8UC3.at<cv::Vec3b>(i, 0);
for (int i = 0; i < image8UC3.rows; i++)
image32FC3.at<cv::Vec3f>(i, 0) = image8UC3.at<cv::Vec3b>(i, 0);
apply(image32FC3, num_cluster, color_space);
repalce_centers_aplha(ori_image, new_image);
@ -43,16 +44,25 @@ public:
convert_color_space(this->m_centers8UC3, this->m_centers8UC3, color_space, true);
}
void apply(const std::vector<std::array<float, 4>> &ori_colors,
std::vector<std::array<float, 4>> & cluster_results,
std::vector<int> & labels,
int num_cluster = -1,
int max_cluster = 15,
int color_space = 2)
{
// 0~255
cv::Mat flatten_image8UC3 = flatten_vector(ori_colors);
this->apply(flatten_image8UC3, cluster_results, labels, num_cluster, max_cluster, color_space);
}
void apply(const cv::Mat & flatten_image8UC3,
std::vector<std::array<float, 4>> &cluster_results,
std::vector<int> & labels,
int num_cluster = -1,
int max_cluster = 15,
int color_space = 2)
{
cv::Mat image8UC3;
convert_color_space(flatten_image8UC3, image8UC3, color_space);
@ -60,36 +70,44 @@ public:
for (int i = 0; i < image8UC3.rows; i++)
image32FC3.at<cv::Vec3f>(i, 0) = image8UC3.at<cv::Vec3b>(i, 0);
int best_cluster = 1;
double cur_score, best_score = 100;
int max_cluster = ori_colors.size();
num_cluster = fmin(num_cluster, max_cluster);
int best_cluster = 1;
double cur_score = 0, best_score = 100;
num_cluster = fmin(num_cluster, max_cluster);
if (num_cluster < 1) {
cur_score = kmeans(image32FC3, 1, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS);
if (!this->more_than_request(image8UC3, max_cluster)) max_cluster = compute_num_colors(image8UC3);
num_cluster = fmin(num_cluster, max_cluster);
cur_score = cv::kmeans(image32FC3, 1, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS);
best_score = cur_score;
for (int cur_cluster = 2; cur_cluster < 16; cur_cluster++) {
if (cur_cluster > max_cluster)
for (int cur_cluster = 2; cur_cluster < max_cluster + 1; cur_cluster++) {
cv::Mat centers32FC3;
cur_score = cv::kmeans(image32FC3, cur_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3,
cv::KMEANS_PP_CENTERS, centers32FC3);
if (this->repeat_center(cur_cluster, centers32FC3, color_space))
break;
cur_score = kmeans(image32FC3, cur_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3,
cv::KMEANS_PP_CENTERS);
best_cluster = cur_score < best_score ? cur_cluster : best_cluster;
best_score = cur_score < best_score ? cur_score : best_score;
}
} else
} else if (this->more_than_request(image8UC3, num_cluster))
best_cluster = num_cluster;
else {
best_cluster = compute_num_colors(image8UC3);
std::cout << "num of image color is " << best_cluster << ", less than custom number " << num_cluster << std::endl;
}
cv::Mat centers32FC3;
kmeans(image32FC3, best_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS,
centers32FC3);
cv::kmeans(image32FC3, best_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS,
centers32FC3);
this->m_centers8UC3 = cv::Mat(best_cluster, 1, CV_8UC3);
for (int i = 0; i < best_cluster; i++)
this->m_centers8UC3.at<cv::Vec3b>(i) = centers32FC3.at<cv::Vec3f>(i);
for (int i = 0; i < best_cluster; i++) {
auto center = centers32FC3.row(i);
this->m_centers8UC3.at<cv::Vec3b>(i) = {uchar(center.at<float>(0)), uchar(center.at<float>(1)), uchar(center.at<float>(2))};
}
convert_color_space(this->m_centers8UC3, this->m_centers8UC3, color_space, true);
cluster_results.clear();
labels.clear();
for (int i = 0; i < ori_colors.size(); i++)
for (int i = 0; i < flatten_image8UC3.rows; i++)
labels.emplace_back(this->m_flatten_labels.at<int>(i, 0));
for (int i = 0; i < best_cluster; i++) {
cv::Vec3f center = this->m_centers8UC3.at<cv::Vec3b>(i, 0);
@ -97,6 +115,59 @@ public:
}
}
bool more_than_request(const cv::Mat &image8UC3, int target_num)
{
std::vector<cv::Vec3b> uniqueImage;
cv::Vec3b cur_color;
for (int i = 0; i < image8UC3.rows; i++) {
cur_color = image8UC3.at<cv::Vec3b>(i, 0);
if (!is_in(cur_color, uniqueImage)) {
uniqueImage.emplace_back(cur_color);
if (uniqueImage.size() >= target_num) return true;
}
}
return false;
}
int compute_num_colors(const cv::Mat &image8UC3)
{
std::vector<cv::Vec3b> uniqueImage;
cv::Vec3b cur_color;
for (int i = 0; i < image8UC3.rows; i++) {
cur_color = image8UC3.at<cv::Vec3b>(i, 0);
if (!is_in(cur_color, uniqueImage)) uniqueImage.emplace_back(cur_color);
}
return uniqueImage.size();
}
bool is_in(const cv::Vec3b &cur_color, const std::vector<cv::Vec3b> &uniqueImage)
{
for (auto &color : uniqueImage)
if (cur_color[0] == color[0] && cur_color[1] == color[1] && cur_color[2] == color[2]) return true;
return false;
}
bool repeat_center(int cur_cluster, const cv::Mat &centers32FC3, int color_space)
{
cv::Mat centers8UC3 = cv::Mat(cur_cluster, 1, CV_8UC3);
for (int i = 0; i < cur_cluster; i++) {
auto center = centers32FC3.row(i);
centers8UC3.at<cv::Vec3b>(i) = {uchar(center.at<float>(0)), uchar(center.at<float>(1)), uchar(center.at<float>(2))};
}
convert_color_space(centers8UC3, centers8UC3, color_space, true);
std::vector<cv::Vec3b> unique_centers;
cv::Vec3b cur_center;
for (int i = 0; i < cur_cluster; i++) {
cur_center = centers8UC3.at<cv::Vec3b>(i, 0);
if (!is_in(cur_center, unique_centers))
unique_centers.emplace_back(cur_center);
else
return true;
}
return false;
}
void replace_centers(cv::Mat &ori_image, cv::Mat &new_image)
{
for (int i = 0; i < ori_image.rows; i++) {
@ -126,7 +197,7 @@ public:
}
}
void convert_color_space(cv::Mat &ori_image, cv::Mat &image, int color_space, bool reverse = false)
void convert_color_space(const cv::Mat &ori_image, cv::Mat &image, int color_space, bool reverse = false)
{
switch (color_space) {
case 0: image = ori_image; break;