我正在尝试检测人们穿过空间然后为每个人分别在“水族馆”中展示鱼的动作。现在我们正在使用Processing和OpenCV进行面部检测，然后为每张脸创造一条鱼。
问题是系统以非常低的帧速率运行。我们需要将帧速率提高一个很大的因素，这就是我们试图弄清楚如何使用运动检测的原因。
我们的老师建议我们在处理过程中使用线程，并且不经常检查人员，但我们对如何进行线程操作感到困惑。
关于我们应该如何处理这个问题的任何建议都会非常感激。谢谢。
以下是代码：
import hypermedia.video.*; // Imports the OpenCV library
import java.awt.Rectangle;
import ddf.minim.analysis.*;
import ddf.minim.*;
OpenCV opencv; // Creates a new OpenCV object
Minim minim;
AudioInput in;
FFT fft;
int w;
PImage fade;
PImage movementImg; // Creates a new PImage to hold the movement image
ArrayList bubbles; // Creates an ArrayList to hold the Bubble objects
PImage bubblePNG; // Creates a PImage that will hold the image of the bubble
int randPos;
PImage fishImg;
PImage fishImg2;
PImage fishImg3;
PImage fishImg4;
PImage fishImg5;
PImage sharkImg;
PImage clockImg;
PImage backImg;
int sharkX=480;
int sharkY=height/2;
int sharkMoves = 480;
int sharkSpeed=40;
int flagForShark=0;
int flagForNotification=0;
ArrayList psystems;
int NotificationX = 10;
int NotificationY = 10;
//clock
int cx, cy;
float secondsRadius;
float minutesRadius;
float hoursRadius;
float clockDiameter;
void setup(){
size ( 640, 480 ); // Window size of 640 x 480
opencv = new OpenCV( this ); // Initialises the OpenCV library
opencv.capture( 640, 480 ); // Sets the capture size to 640 x 480
opencv.cascade( OpenCV.CASCADE_FRONTALFACE_ALT ); //// load the FRONTALFACE description file
movementImg = new PImage(640, 480 ); // Initialises the PImage that holds the movement image
bubbles = new ArrayList(); // Initialises the ArrayList
bubblePNG = loadImage("bubble.png"); // Load the bubble image into memory
smooth();
fishImg = loadImage("purpleFish.png");
fishImg2 = loadImage("fish2.png");
fishImg3 = loadImage("fish3.png");
fishImg4 = loadImage("fish4.png");
fishImg5 = loadImage("fish5.png");
sharkImg = loadImage("shark.png");
clockImg = loadImage("clock.png");
backImg = loadImage("bg01.png");
fill(61,36,9);
int radius = min(100, 100) / 2;
secondsRadius = radius * 0.72;
minutesRadius = radius * 0.60;
hoursRadius = radius * 0.50;
clockDiameter = radius * 1.8;
cx = 50;
cy = 50;
//Sound stuff
minim = new Minim(this);
in = minim.getLineIn(Minim.STEREO, 512);
fft = new FFT(in.bufferSize(),in.sampleRate());
fft.logAverages(60,7);
}
void youareloud(){
fft.forward(in.mix);
for(int i=0; i<fft.avgSize();i++){
if(fft.getAvg(i) > 3){
randPos = 160*(int)random(0, 5);
bubbles.add(new Bubble( randPos+(int)random(-10, 10), 480, (int)random(10,25), (int)random(10,25))); // Adds a new bubble to the array with a random x position
}
}
for ( int i = 0; i < bubbles.size(); i++ ){ // For every bubble in the bubbles array
Bubble _bubble = (Bubble) bubbles.get(i); // Copies the current bubble into a temporary object
if(_bubble.update() == 1){ // If the bubble's update function returns '1'
bubbles.remove(i); // then remove the bubble from the array
_bubble = null; // and make the temporary bubble object null
i--; // since we've removed a bubble from the array, we need to subtract 1 from i, or we'll skip the next bubble
}else{ // If the bubble's update function doesn't return '1'
bubbles.set(i, _bubble); // Copys the updated temporary bubble object back into the array
_bubble = null; // Makes the temporary bubble object null.
}
}
}
void draw(){
opencv.read(); // Captures a frame from the camera
opencv.flip(OpenCV.FLIP_HORIZONTAL); // Flips the image horizontally
// background(loadImage("data/underwater_640x480_stretched.jpg"));//drwa detected environemtn
background(backImg);
faces();
youareloud();
extras();
}
class Bubble{
int bubbleX, bubbleY, bubbleWidth, bubbleHeight; //Some variables to hold information about the bubble
int randSize = (int)random(10, 20);
Bubble ( int bX, int bY, int bW, int bH ){ //The class constructor- sets the values when a new bubble object is made
bubbleX = bX;
bubbleY = bY;
bubbleWidth = bW;
bubbleHeight = bH;
}
int update(){ //The Bubble update function
int movementAmount; //Create and set a variable to hold the amount of white pixels detected in the area where the bubble is
movementAmount = 0;
for( int y = bubbleY; y < (bubbleY + (bubbleHeight-1)); y++ ){
//For loop that cycles through all of the pixels in the area the bubble occupies
for( int x = bubbleX; x < (bubbleX + (bubbleWidth-1)); x++ ){
if ( x < width && x > 0 && y < height && y > 0 ){
//If the current pixel is within the screen bondaries
if (brightness(movementImg.pixels[x + (y * width)]) > 127){
//and if the brightness is above 127 (in this case, if it is white)
movementAmount++;
//Add 1 to the movementAmount variable.
}
}
}
}
if (movementAmount > 5){ // If more than 5 pixels of movement are detected in the bubble area
//poppedBubbles++; // Add 1 to the variable that holds the number of popped bubbles
return 1; // Return 1 so that the bubble object is destroyed
} else { // If less than 5 pixels of movement are detected,
//bubbleY += 10; // increase the y position of the bubble so that it falls down
bubbleY -= 10; // increase the y position of the bubble so that it falls down
if (bubbleY < 0){ // If the bubble has dropped off of the bottom of the screen
return 1; // Return '1' so that the bubble object is destroyed
}
image(bubblePNG, bubbleX, bubbleY,randSize,randSize); // Draws the bubble to the screen
return 0; // Returns '0' so that the bubble isn't destroyed
}
}
}
void faces(){
Rectangle[] faces = opencv.detect();
noFill();
stroke(255,0,0);
opencv.absDiff(); // Creates a difference image
opencv.convert(OpenCV.GRAY); // Converts to greyscale
opencv.blur(OpenCV.BLUR, 3); // Blur to remove camera noise
opencv.threshold(20); // Thresholds to convert to black and white
movementImg = opencv.image(); // Puts the OpenCV buffer into an image object
opencv.remember(OpenCV.SOURCE, OpenCV.FLIP_HORIZONTAL); // Remembers the camera image so we can generate a difference image next frame. Since we've
for( int i=0; i<faces.length; i++ ) {
//image( opencv.image(), faces[i].x, faces[i].y, faces[i].width, faces[i].height ); // display the image in memory on the right
// opencv.loadImage( "/Users/sang/Desktop/home.png", ); // load image from file
// opencv.convert( GRAY );
// opencv.ROI( faces[i].x, faces[i].y, faces[i].width, faces[i].height );
// opencv.brightness( 80 );
// opencv.contrast( 90 );
if(i==0)
{ image( fishImg,faces[i].x, faces[i].y, faces[i].width, faces[i].height); }
else if(i==1)
{ image( fishImg2,faces[i].x, faces[i].y, faces[i].width, faces[i].height); }
else if(i==2)
{ image( fishImg3,faces[i].x, faces[i].y, faces[i].width, faces[i].height); }
else if(i==3)
{ image( fishImg4,faces[i].x, faces[i].y, faces[i].width, faces[i].height); }
else if(i==4)
{ image( fishImg5,faces[i].x, faces[i].y, faces[i].width, faces[i].height); }
}
}
void extras(){
if(keyPressed){
if (key == 's' || key == 'S'){
flagForShark=1;
} else if(key=='n' || key =='N'){
flagForNotification=1;
} else if(key=='x' || key =='x'){
flagForNotification=0;
}
}
if(flagForShark==1){
// fill(255, 204, 255);
// stroke(128, 0, 128);
image( sharkImg,sharkMoves,sharkY);
//ellipse(candyX,candyY+candyMoves, 55, 55);
//image(loadImage("/Users/sang/Desktop/candy.png"),candyX,candyY+candyMoves);
if(sharkMoves>0){
sharkMoves-=sharkSpeed;
} else {
sharkMoves=480;
flagForShark=0;
}
}
if(flagForNotification==1){
image(sharkImg,NotificationX,NotificationY);
}
//Clock
// Draw the clock background
// fill(80);
noStroke();
// ellipse(cx, cy, clockDiameter, clockDiameter);
image(clockImg,5,5,clockDiameter,clockDiameter);
// Angles for sin() and cos() start at 3 o'clock;
// subtract HALF_PI to make them start at the top
float s = map(second(), 0, 60, 0, TWO_PI) - HALF_PI;
float m = map(minute() + norm(second(), 0, 60), 0, 60, 0, TWO_PI) - HALF_PI;
float h = map(hour() + norm(minute(), 0, 60), 0, 24, 0, TWO_PI * 2) - HALF_PI;
// Draw the hands of the clock
stroke(61,36,9);
strokeWeight(1);
line(cx, cy, cx + cos(s) * secondsRadius, cy + sin(s) * secondsRadius);
strokeWeight(2);
line(cx, cy, cx + cos(m) * minutesRadius, cy + sin(m) * minutesRadius);
strokeWeight(4);
line(cx, cy, cx + cos(h) * hoursRadius, cy + sin(h) * hoursRadius);
// Draw the minute ticks
// strokeWeight(2);
// beginShape(POINTS);
// for (int a = 0; a < 360; a+=6) {
// float x = cx + cos(radians(a)) * secondsRadius;
// float y = cy + sin(radians(a)) * secondsRadius;
// vertex(x, y);
// }
endShape();
//end of clock
}
答案 0 :(得分：3)
我在草图中看到的问题是，您的分析和渲染以相同的帧速率运行。在解决延迟问题时，我建议通过构建由OSC链接的两个草图来实现分而治之的方法。在单台机器上运行的OSC足够快，不会引入额外的延迟问题。这是我如何构建两个草图：
处理草图，其中获取图像数据并进行面部跟踪。该草图每n秒触发一次OSC事件。每个事件都是一个绘制鱼的位置列表。将此值设置为4帧/秒即可开始。
一个处理草图，它从草图1中侦听OSC事件并每隔n秒渲染一次水族箱。将其设置为15帧/秒即可开始。
我在一个类似的问题中使用了这种方法（跟踪帧内最亮的点，当点击到某些坐标时触发声音事件），并且支付了与渲染率分开调整分析率。
希望有所帮助 - 如果您遇到OSC问题，请回火。