opencv将像素存入链表
时间: 2023-05-31 13:06:02 浏览: 55
要将像素存入链表,可以在C++中使用STL的链表容器。首先,定义一个名为Pixel的结构体,用于存储像素的坐标和颜色信息:
```c++
struct Pixel {
int x;
int y;
cv::Vec3b color;
};
```
然后,创建一个链表容器并将像素添加到容器中:
```c++
std::list<Pixel> pixelList;
// 将像素添加到链表中
Pixel pixel;
pixel.x = 10;
pixel.y = 20;
pixel.color = cv::Vec3b(255, 0, 0); // 蓝色
pixelList.push_back(pixel);
```
可以使用类似的方法添加更多像素。可以使用迭代器遍历链表并访问每个像素:
```c++
// 遍历链表并输出每个像素的坐标和颜色信息
for (std::list<Pixel>::iterator it = pixelList.begin(); it != pixelList.end(); ++it) {
std::cout << "x: " << it->x << ", y: " << it->y << ", color: (" << (int)it->color[0] << ", " << (int)it->color[1] << ", " << (int)it->color[2] << ")" << std::endl;
}
```
这样就可以将像素存入链表中并访问它们的信息。
相关问题
用c++语言在opencv将像素的坐标和梯度信息存入链表
首先,需要定义链表节点的数据结构,包括像素坐标和梯度信息:
```c
typedef struct pixelNode {
int x;
int y;
float dx;
float dy;
struct pixelNode* next;
} PixelNode;
```
然后,可以通过遍历图像的每个像素,获取该像素的坐标和梯度信息,并将其存入链表中:
```c
PixelNode* head = NULL; // 链表头指针
for (int y = 0; y < img.rows; y++) {
for (int x = 0; x < img.cols; x++) {
float dx = 0.0, dy = 0.0;
if (x > 0 && x < img.cols - 1 && y > 0 && y < img.rows - 1) {
dx = img.at<uchar>(y, x + 1) - img.at<uchar>(y, x - 1);
dy = img.at<uchar>(y + 1, x) - img.at<uchar>(y - 1, x);
}
PixelNode* node = (PixelNode*)malloc(sizeof(PixelNode));
node->x = x;
node->y = y;
node->dx = dx;
node->dy = dy;
node->next = head;
head = node;
}
}
```
在此基础上,可以进一步封装成函数,方便调用:
```c
PixelNode* getPixelList(cv::Mat& img) {
PixelNode* head = NULL;
for (int y = 0; y < img.rows; y++) {
for (int x = 0; x < img.cols; x++) {
float dx = 0.0, dy = 0.0;
if (x > 0 && x < img.cols - 1 && y > 0 && y < img.rows - 1) {
dx = img.at<uchar>(y, x + 1) - img.at<uchar>(y, x - 1);
dy = img.at<uchar>(y + 1, x) - img.at<uchar>(y - 1, x);
}
PixelNode* node = (PixelNode*)malloc(sizeof(PixelNode));
node->x = x;
node->y = y;
node->dx = dx;
node->dy = dy;
node->next = head;
head = node;
}
}
return head;
}
```
用c++语言在opencv将图片像素的坐标和梯度信息存入链表并显示链表
首先,需要安装并配置好OpenCV库。然后可以按照以下步骤实现:
1. 定义链表结构体,包括像素坐标和梯度信息:
```c
typedef struct Node {
int x;
int y;
double dx;
double dy;
struct Node* next;
} Node;
```
2. 定义函数来读取图片、计算像素梯度并存入链表中:
```c
void get_pixel_gradient(char* img_path, Node** head) {
Mat img = imread(img_path, IMREAD_GRAYSCALE);
if (img.empty()) {
printf("Error: failed to load image\n");
return;
}
Mat dx, dy;
Sobel(img, dx, CV_64F, 1, 0);
Sobel(img, dy, CV_64F, 0, 1);
*head = NULL;
Node* tail = NULL;
for (int i = 0; i < img.rows; i++) {
for (int j = 0; j < img.cols; j++) {
double dx_val = dx.at<double>(i, j);
double dy_val = dy.at<double>(i, j);
Node* node = (Node*)malloc(sizeof(Node));
node->x = j;
node->y = i;
node->dx = dx_val;
node->dy = dy_val;
node->next = NULL;
if (*head == NULL) {
*head = node;
tail = node;
} else {
tail->next = node;
tail = node;
}
}
}
}
```
3. 定义函数来显示链表中的像素坐标和梯度信息:
```c
void show_pixel_gradient(Node* head) {
Mat img(480, 640, CV_8UC3, Scalar(0, 0, 0));
Node* node = head;
while (node != NULL) {
int x = node->x;
int y = node->y;
double dx = node->dx;
double dy = node->dy;
if (dx > 0) {
line(img, Point(x, y), Point(x + dx, y), Scalar(0, 0, 255), 1);
} else {
line(img, Point(x, y), Point(x + dx, y), Scalar(255, 0, 0), 1);
}
if (dy > 0) {
line(img, Point(x, y), Point(x, y + dy), Scalar(0, 0, 255), 1);
} else {
line(img, Point(x, y), Point(x, y + dy), Scalar(255, 0, 0), 1);
}
node = node->next;
}
namedWindow("Pixel Gradient", WINDOW_NORMAL);
imshow("Pixel Gradient", img);
waitKey(0);
}
```
4. 在主函数中调用这两个函数并释放链表内存:
```c
int main() {
Node* head = NULL;
get_pixel_gradient("test.jpg", &head);
show_pixel_gradient(head);
Node* node = head;
while (node != NULL) {
Node* temp = node;
node = node->next;
free(temp);
}
return 0;
}
```
这样就可以读取图片,计算像素梯度并存入链表中,然后显示链表中的像素坐标和梯度信息。注意需要在最后释放链表内存以避免内存泄漏。