Im trying to add settings to a snake game made in processing. I want to have something like easy, normal and hard or something along the lines of that and change the speed and maybe size of the grid. If anyone coudl explain how to id greatly appreciate it!
ArrayList<Integer> x = new ArrayList<Integer>(), y = new ArrayList<Integer>();
int w = 30, h = 30, bs = 20, dir = 2, applex = 12, appley = 10;
int[] dx = {0,0,1,-1}, dy = {1,-1,0,0};
boolean gameover = false;
void setup() {
size(600,600);
x.add(5);
y.add(5);
}
void draw() {
background(255);
for(int i = 0 ; i < w; i++) line(i*bs, 0, i*bs, height); //Vertical line for grid
for(int i = 0 ; i < h; i++) line(0, i*bs, width, i*bs); //Horizontal line for grid
for(int i = 0 ; i < x.size(); i++) {
fill (0,255,0);
rect(x.get(i)*bs, y.get(i)*bs, bs, bs);
}
if(!gameover) {
fill(255,0,0);
rect(applex*bs, appley*bs, bs, bs);
if(frameCount%5==0) {
x.add(0,x.get(0) + dx[dir]);
y.add(0,y.get(0) + dy[dir]);
if(x.get(0) < 0 || y.get(0) < 0 || x.get(0) >= w || y.get(0) >= h) gameover = true;
for(int i = 1; i < x.size(); i++) if(x.get(0) == x.get(i) && y.get(0) == y.get(i)) gameover = true;
if(x.get(0)==applex && y.get(0)==appley) {
applex = (int)random(0,w);
appley = (int)random(0,h);
}else {
x.remove(x.size()-1);
y.remove(y.size()-1);
}
}
} else {
fill(0);
textSize(30);
text("GAME OVER. Press Space to Play Again", 20, height/2);
if(keyPressed && key == ' ') {
x.clear(); //Clear array list
y.clear(); //Clear array list
x.add(5);
y.add(5);
gameover = false;
}
}
if (keyPressed == true) {
int newdir = key=='s' ? 0 : (key=='w' ? 1 : (key=='d' ? 2 : (key=='a' ? 3 : -1)));
if(newdir != -1 && (x.size() <= 1 || !(x.get(1) ==x.get(0) + dx[newdir] && y.get (1) == y.get(0) + dy[newdir]))) dir = newdir;
}
}
You need to break your problem down into smaller steps:
Step one: Can you store the difficulty in a variable? This might be an int that keeps track of a level, or a boolean that switches between easy and hard. Just hardcode the value of that variable for now.
Step two: Can you write your code so it changes behavior based on the difficulty level? Use the variable you created in step one. You might use an if statement to check the difficulty level, or maybe the speed increases over time. It's completely up to you. Start out with a hard-coded value. Change the value to see different behaviors.
Step three: Can you programatically change that value? Maybe this requires a settings screen where the user chooses the difficulty, or maybe it gets more difficult over time. But you have to do the first two steps before you can start this step.
If you get stuck on a specific step, then post an MCVE and we'll go from there.
int x = 31;
int y = 31;
int x_dir = 4;
int y_dir = 0;
void setup ()
{
size (800, 800);
}
void draw ()
{
background (150);
ellipse (x,y,60, 60);
if (x+30>=width)
{
x_dir =-4;
y_dir = 4;
}
if (y+30>=height)
{
x_dir=4;
y_dir = 0;
}
if (x+30>=width)
{
x_dir = -4;
}
x+=x_dir;
y+=y_dir;
println(x,y);
}
Hi,
I have to create this program in processing which produces an animation of a ball going in a Z pattern (top left to top right, diagonal top right to bottom left, and then straight from bottom left to bottom right) which then goes backwards along the same path it came.
While I have the code written out for the forward direction, I don't know what 2 if or else statements I need to write for the program so that based on one condition it goes forwards, and based on another condition it will go backwards, and it will continue doing so until it terminates.
If I am able to figure out which two if statements I need to write, all I need to do is copy and reverse the x_dir and y_dir signs on the forward loop.
There are a ton of different ways you can do this.
One approach is to keep track of which "mode" you're in. You could do this using an int variable that's 0 when you're on the first part of the path, 1 when you're on the second part of the path, etc. Then just use an if statement to decide what to do, how to move the ball, etc.
Here's an example:
int x = 31;
int y = 31;
int mode = 0;
void setup ()
{
size (800, 800);
}
void draw ()
{
background (150);
ellipse (x, y, 60, 60);
if (mode == 0) {
x = x + 4;
if (x+30>=width) {
mode = 1;
}
} else if (mode == 1) {
x = x - 4;
y = y + 4;
if (y+30>=height) {
mode = 2;
}
} else if (mode == 2) {
x = x + 4;
if (x+30>=width) {
mode = 3;
}
} else if (mode == 3) {
x = x - 4;
y = y - 4;
if (y-30 < 0) {
mode = 2;
}
}
}
Like I said, this is only one way to approach the problem, and there are some obvious improvements you could make. For example, you could store the movement speeds and the conditions that change the mode in an array (or better yet, in objects) and get rid of all of the if statements.
I have created a Space Invaders game in which the player must shoot an asteroid which displays a random number. A sum will also be randomly generated at the start of the scene. Once the player shoots an asteroid the scene reloads, with points awarded for correct answers.
The problem I am having is that I need at least one asteroid to display the correct answer. I am currently achieving this by reloading the scene until an asteroids number matches the answer to the sum. This can take quite a few reloads and looks really bad. Is there a better way to achive this which will look better and be more efficient. I have included my effort below. I appreciate any comments. Thanks!
Script for checking the correct answer and reloading the scene.
#pragma strict
function Start ()
{
}
{
if (
Asteroid1_Script.asteroid1Value != (Sum_Script.sumA - Sum_Script.sumB) &&
Asteroid2_Script.asteroid2Value != (Sum_Script.sumA - Sum_Script.sumB) &&
Asteroid3_Script.asteroid3Value != (Sum_Script.sumA - Sum_Script.sumB) &&
Asteroid4_Script.asteroid4Value != (Sum_Script.sumA - Sum_Script.sumB) &&
Asteroid5_Script.asteroid5Value != (Sum_Script.sumA - Sum_Script.sumB)
)
{
Application.LoadLevel("L1");
}
}
Script for randomly generating the sum.
#pragma strict
static var sumA :int = 0;
static var sumB :int = 0;
function Start ()
{
var newSumA = Random.Range(6,10);
sumA = newSumA;
var newSumB = Random.Range(1,6);
sumB = newSumB;
}
function Update () {
//Question Output.
guiText.text = sumA.ToString() + " - " + sumB.ToString()+ " =";
}
Script for generating an asteroids random number.
#pragma strict
var mainCam: Camera;
static var asteroid1Value : int = 0;
var asteroid1 : Transform;
var Asteroid1Style : GUIStyle;
function Start ()
{
var newAsteroid1Value = Random.Range(0,10);
asteroid1Value = newAsteroid1Value;
asteroid1.position.x = mainCam.ScreenToWorldPoint (new Vector3 (160f, 0f, 0f)).x;
asteroid1.position.y = mainCam.ScreenToWorldPoint (new Vector3 (0f, 450f, 0f)).y;
}
function OnGUI()
{
var point = Camera.main.WorldToScreenPoint(transform.position);
GUI.Label(new Rect(point.x, Screen.currentResolution.height - point.y - 530, 110, 100), asteroid1Value.ToString(), Asteroid1Style);
}
function OnCollisionEnter(col : Collision)
{
if(asteroid1Value == (Sum_Script.sumA - Sum_Script.sumB))
{
Destroy(gameObject);
Score_Script.score ++;
}
if(asteroid1Value != (Sum_Script.sumA - Sum_Script.sumB))
{
Score_Script.score --;
}
}
Do as you are doing, generate 5 random numbers for your asteroids.
Then generate a random number between 1 and 5, this is your random asteroid, and then set its value to the answer. (sumA - sumB)
You just need to abstract your logic.
The best argument I can make is, simply put, build your random numbers before you build your asteroids.
That way, you always have a correct one.
I would simply code:
function start(){
var x = 5 //X being whatever number of asteroids you wish.
var a = new Array();
for(var i=0; i<x; i++){
a[i] = Random.Range(0,10);
}
for( i in a){ buildAsteroid(a[i]) }
}
And... if the number matches, success.
Does anybody know how to find the local maxima in a grayscale IPL_DEPTH_8U image using OpenCV? HarrisCorner mentions something like that but I'm actually not interested in corners ...
Thanks!
A pixel is considered a local maximum if it is equal to the maximum value in a 'local' neighborhood. The function below captures this property in two lines of code.
To deal with pixels on 'plateaus' (value equal to their neighborhood) one can use the local minimum property, since plateaus pixels are equal to their local minimum. The rest of the code filters out those pixels.
void non_maxima_suppression(const cv::Mat& image, cv::Mat& mask, bool remove_plateaus) {
// find pixels that are equal to the local neighborhood not maximum (including 'plateaus')
cv::dilate(image, mask, cv::Mat());
cv::compare(image, mask, mask, cv::CMP_GE);
// optionally filter out pixels that are equal to the local minimum ('plateaus')
if (remove_plateaus) {
cv::Mat non_plateau_mask;
cv::erode(image, non_plateau_mask, cv::Mat());
cv::compare(image, non_plateau_mask, non_plateau_mask, cv::CMP_GT);
cv::bitwise_and(mask, non_plateau_mask, mask);
}
}
Here's a simple trick. The idea is to dilate with a kernel that contains a hole in the center. After the dilate operation, each pixel is replaced with the maximum of it's neighbors (using a 5 by 5 neighborhood in this example), excluding the original pixel.
Mat1b kernelLM(Size(5, 5), 1u);
kernelLM.at<uchar>(2, 2) = 0u;
Mat imageLM;
dilate(image, imageLM, kernelLM);
Mat1b localMaxima = (image > imageLM);
Actually after I posted the code above I wrote a better and very very faster one ..
The code above suffers even for a 640x480 picture..
I optimized it and now it is very very fast even for 1600x1200 pic.
Here is the code :
void localMaxima(cv::Mat src,cv::Mat &dst,int squareSize)
{
if (squareSize==0)
{
dst = src.clone();
return;
}
Mat m0;
dst = src.clone();
Point maxLoc(0,0);
//1.Be sure to have at least 3x3 for at least looking at 1 pixel close neighbours
// Also the window must be <odd>x<odd>
SANITYCHECK(squareSize,3,1);
int sqrCenter = (squareSize-1)/2;
//2.Create the localWindow mask to get things done faster
// When we find a local maxima we will multiply the subwindow with this MASK
// So that we will not search for those 0 values again and again
Mat localWindowMask = Mat::zeros(Size(squareSize,squareSize),CV_8U);//boolean
localWindowMask.at<unsigned char>(sqrCenter,sqrCenter)=1;
//3.Find the threshold value to threshold the image
//this function here returns the peak of histogram of picture
//the picture is a thresholded picture it will have a lot of zero values in it
//so that the second boolean variable says :
// (boolean) ? "return peak even if it is at 0" : "return peak discarding 0"
int thrshld = maxUsedValInHistogramData(dst,false);
threshold(dst,m0,thrshld,1,THRESH_BINARY);
//4.Now delete all thresholded values from picture
dst = dst.mul(m0);
//put the src in the middle of the big array
for (int row=sqrCenter;row<dst.size().height-sqrCenter;row++)
for (int col=sqrCenter;col<dst.size().width-sqrCenter;col++)
{
//1.if the value is zero it can not be a local maxima
if (dst.at<unsigned char>(row,col)==0)
continue;
//2.the value at (row,col) is not 0 so it can be a local maxima point
m0 = dst.colRange(col-sqrCenter,col+sqrCenter+1).rowRange(row-sqrCenter,row+sqrCenter+1);
minMaxLoc(m0,NULL,NULL,NULL,&maxLoc);
//if the maximum location of this subWindow is at center
//it means we found the local maxima
//so we should delete the surrounding values which lies in the subWindow area
//hence we will not try to find if a point is at localMaxima when already found a neighbour was
if ((maxLoc.x==sqrCenter)&&(maxLoc.y==sqrCenter))
{
m0 = m0.mul(localWindowMask);
//we can skip the values that we already made 0 by the above function
col+=sqrCenter;
}
}
}
The following listing is a function similar to Matlab's "imregionalmax". It looks for at most nLocMax local maxima above threshold, where the found local maxima are at least minDistBtwLocMax pixels apart. It returns the actual number of local maxima found. Notice that it uses OpenCV's minMaxLoc to find global maxima. It is "opencv-self-contained" except for the (easy to implement) function vdist, which computes the (euclidian) distance between points (r,c) and (row,col).
input is one-channel CV_32F matrix, and locations is nLocMax (rows) by 2 (columns) CV_32S matrix.
int imregionalmax(Mat input, int nLocMax, float threshold, float minDistBtwLocMax, Mat locations)
{
Mat scratch = input.clone();
int nFoundLocMax = 0;
for (int i = 0; i < nLocMax; i++) {
Point location;
double maxVal;
minMaxLoc(scratch, NULL, &maxVal, NULL, &location);
if (maxVal > threshold) {
nFoundLocMax += 1;
int row = location.y;
int col = location.x;
locations.at<int>(i,0) = row;
locations.at<int>(i,1) = col;
int r0 = (row-minDistBtwLocMax > -1 ? row-minDistBtwLocMax : 0);
int r1 = (row+minDistBtwLocMax < scratch.rows ? row+minDistBtwLocMax : scratch.rows-1);
int c0 = (col-minDistBtwLocMax > -1 ? col-minDistBtwLocMax : 0);
int c1 = (col+minDistBtwLocMax < scratch.cols ? col+minDistBtwLocMax : scratch.cols-1);
for (int r = r0; r <= r1; r++) {
for (int c = c0; c <= c1; c++) {
if (vdist(Point2DMake(r, c),Point2DMake(row, col)) <= minDistBtwLocMax) {
scratch.at<float>(r,c) = 0.0;
}
}
}
} else {
break;
}
}
return nFoundLocMax;
}
The first question to answer would be what is "local" in your opinion. The answer may well be a square window (say 3x3 or 5x5) or circular window of a certain radius. You can then scan over the entire image with the window centered at each pixel and pick the highest value in the window.
See this for how to access pixel values in OpenCV.
This is very fast method. It stored founded maxima in a vector of
Points.
vector <Point> GetLocalMaxima(const cv::Mat Src,int MatchingSize, int Threshold, int GaussKernel )
{
vector <Point> vMaxLoc(0);
if ((MatchingSize % 2 == 0) || (GaussKernel % 2 == 0)) // MatchingSize and GaussKernel have to be "odd" and > 0
{
return vMaxLoc;
}
vMaxLoc.reserve(100); // Reserve place for fast access
Mat ProcessImg = Src.clone();
int W = Src.cols;
int H = Src.rows;
int SearchWidth = W - MatchingSize;
int SearchHeight = H - MatchingSize;
int MatchingSquareCenter = MatchingSize/2;
if(GaussKernel > 1) // If You need a smoothing
{
GaussianBlur(ProcessImg,ProcessImg,Size(GaussKernel,GaussKernel),0,0,4);
}
uchar* pProcess = (uchar *) ProcessImg.data; // The pointer to image Data
int Shift = MatchingSquareCenter * ( W + 1);
int k = 0;
for(int y=0; y < SearchHeight; ++y)
{
int m = k + Shift;
for(int x=0;x < SearchWidth ; ++x)
{
if (pProcess[m++] >= Threshold)
{
Point LocMax;
Mat mROI(ProcessImg, Rect(x,y,MatchingSize,MatchingSize));
minMaxLoc(mROI,NULL,NULL,NULL,&LocMax);
if (LocMax.x == MatchingSquareCenter && LocMax.y == MatchingSquareCenter)
{
vMaxLoc.push_back(Point( x+LocMax.x,y + LocMax.y ));
// imshow("W1",mROI);cvWaitKey(0); //For gebug
}
}
}
k += W;
}
return vMaxLoc;
}
Found a simple solution.
In this example, if you are trying to find 2 results of a matchTemplate function with a minimum distance from each other.
cv::Mat result;
matchTemplate(search, target, result, CV_TM_SQDIFF_NORMED);
float score1;
cv::Point displacement1 = MinMax(result, score1);
cv::circle(result, cv::Point(displacement1.x+result.cols/2 , displacement1.y+result.rows/2), 10, cv::Scalar(0), CV_FILLED, 8, 0);
float score2;
cv::Point displacement2 = MinMax(result, score2);
where
cv::Point MinMax(cv::Mat &result, float &score)
{
double minVal, maxVal;
cv::Point minLoc, maxLoc, matchLoc;
minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat());
matchLoc.x = minLoc.x - result.cols/2;
matchLoc.y = minLoc.y - result.rows/2;
return minVal;
}
The process is:
Find global Minimum using minMaxLoc
Draw a filled white circle around global minimum using min distance between minima as radius
Find another minimum
The the scores can be compared to each other to determine, for example, the certainty of the match,
To find more than just the global minimum and maximum try using this function from skimage:
http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.peak_local_max
You can parameterize the minimum distance between peaks, too. And more. To find minima, use negated values (take care of the array type though, 255-image could do the trick).
You can go over each pixel and test if it is a local maxima. Here is how I would do it.
The input is assumed to be type CV_32FC1
#include <vector>//std::vector
#include <algorithm>//std::sort
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core/core.hpp"
//structure for maximal values including position
struct SRegionalMaxPoint
{
SRegionalMaxPoint():
values(-FLT_MAX),
row(-1),
col(-1)
{}
float values;
int row;
int col;
//ascending order
bool operator()(const SRegionalMaxPoint& a, const SRegionalMaxPoint& b)
{
return a.values < b.values;
}
};
//checks if pixel is local max
bool isRegionalMax(const float* im_ptr, const int& cols )
{
float center = *im_ptr;
bool is_regional_max = true;
im_ptr -= (cols + 1);
for (int ii = 0; ii < 3; ++ii, im_ptr+= (cols-3))
{
for (int jj = 0; jj < 3; ++jj, im_ptr++)
{
if (ii != 1 || jj != 1)
{
is_regional_max &= (center > *im_ptr);
}
}
}
return is_regional_max;
}
void imregionalmax(
const cv::Mat& input,
std::vector<SRegionalMaxPoint>& buffer)
{
//find local max - top maxima
static const int margin = 1;
const int rows = input.rows;
const int cols = input.cols;
for (int i = margin; i < rows - margin; ++i)
{
const float* im_ptr = input.ptr<float>(i, margin);
for (int j = margin; j < cols - margin; ++j, im_ptr++)
{
//Check if pixel is local maximum
if ( isRegionalMax(im_ptr, cols ) )
{
cv::Rect roi = cv::Rect(j - margin, i - margin, 3, 3);
cv::Mat subMat = input(roi);
float val = *im_ptr;
//replace smallest value in buffer
if ( val > buffer[0].values )
{
buffer[0].values = val;
buffer[0].row = i;
buffer[0].col = j;
std::sort(buffer.begin(), buffer.end(), SRegionalMaxPoint());
}
}
}
}
}
For testing the code you can try this:
cv::Mat temp = cv::Mat::zeros(15, 15, CV_32FC1);
temp.at<float>(7, 7) = 1;
temp.at<float>(3, 5) = 6;
temp.at<float>(8, 10) = 4;
temp.at<float>(11, 13) = 7;
temp.at<float>(10, 3) = 8;
temp.at<float>(7, 13) = 3;
vector<SRegionalMaxPoint> buffer_(5);
imregionalmax(temp, buffer_);
cv::Mat debug;
cv::cvtColor(temp, debug, cv::COLOR_GRAY2BGR);
for (auto it = buffer_.begin(); it != buffer_.end(); ++it)
{
circle(debug, cv::Point(it->col, it->row), 1, cv::Scalar(0, 255, 0));
}
This solution does not take plateaus into account so it is not exactly the same as matlab's imregionalmax()
I think you want to use the
MinMaxLoc(arr, mask=NULL)-> (minVal, maxVal, minLoc, maxLoc)
Finds global minimum and maximum in array or subarray
function on you image