image – ページ 10 – プログラミング de 落描き

2017年12月7日2017年12月6日

Insta20171206

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[ About ]
画像とパーティクルを組み合わせ。
Image x Particle.

[ Source ]

#pragma once
#include "ofMain.h"
#include "ofFbo.h"
#include "Particle.h"

class ofApp : public ofBaseApp {

public:
	void setup();
	void update();
	void draw();

	void keyPressed(int key) {};
	void keyReleased(int key) {};
	void mouseMoved(int x, int y) {};
	void mouseDragged(int x, int y, int button) {};
	void mousePressed(int x, int y, int button) {};
	void mouseReleased(int x, int y, int button) {};
	void mouseEntered(int x, int y) {};
	void mouseExited(int x, int y) {};
	void windowResized(int w, int h) {};
	void dragEvent(ofDragInfo dragInfo) {};
	void gotMessage(ofMessage msg) {};
	
	ofImage photo;
	ofFbo fbo;
	vector<shared_ptr<Particle>> particles;
};

#pragma once

#include "ofMain.h"

#include "ofFbo.h"

#include "Particle.h"

class ofApp : public ofBaseApp {

public:

void setup();

void update();

void draw();

void keyPressed(int key) {};

void keyReleased(int key) {};

void mouseMoved(int x, int y) {};

void mouseDragged(int x, int y, int button) {};

void mousePressed(int x, int y, int button) {};

void mouseReleased(int x, int y, int button) {};

void mouseEntered(int x, int y) {};

void mouseExited(int x, int y) {};

void windowResized(int w, int h) {};

void dragEvent(ofDragInfo dragInfo) {};

void gotMessage(ofMessage msg) {};

ofImage photo;

ofFbo fbo;

vector<shared_ptr<Particle>> particles;

};

#include "ofApp.h"

//--------------------------------------------------------------
void ofApp::setup() {
	ofSetFrameRate(30);
	ofBackground(0);
	ofSetWindowTitle("Insta");

	this->photo.loadImage("photo.png");

	for (int i = 0; i < 1024 + 512; i++) {
		this->particles.push_back(shared_ptr<Particle>(new Particle()));
	}

	this->fbo.allocate(512, 512);
}

//--------------------------------------------------------------
void ofApp::update() {
	ofPixels pixels = this->photo.getPixelsRef();
	ofColor pixel_color;

	for (int i = 0; i < this->particles.size(); i++) {
		this->particles[i]->update();
	}

	this->fbo.begin();
	ofClear(0);

	ofSetColor(255, 255 * mouseX / 512);
	this->photo.draw(0, 0);

	for (int i = 0; i < this->particles.size(); i++) {
		pixel_color = pixels.getColor(this->particles[i]->get_location().x, this->particles[i]->get_location().y);
		this->particles[i]->draw(this->particles, pixel_color);
	}
	this->fbo.end();
}

//--------------------------------------------------------------
void ofApp::draw() {
	this->fbo.draw(0, 0);
}

//--------------------------------------------------------------
int main() {
	ofSetupOpenGL(512, 512, OF_WINDOW);
	ofRunApp(new ofApp());
}

#include "ofApp.h"

//--------------------------------------------------------------

void ofApp::setup() {

ofSetFrameRate(30);

ofBackground(0);

ofSetWindowTitle("Insta");

this->photo.loadImage("photo.png");

for (int i = 0; i < 1024 + 512; i++) {

this->particles.push_back(shared_ptr<Particle>(new Particle()));

}

this->fbo.allocate(512, 512);

}

//--------------------------------------------------------------

void ofApp::update() {

ofPixels pixels = this->photo.getPixelsRef();

ofColor pixel_color;

for (int i = 0; i < this->particles.size(); i++) {

this->particles[i]->update();

}

this->fbo.begin();

ofClear(0);

ofSetColor(255, 255 * mouseX / 512);

this->photo.draw(0, 0);

for (int i = 0; i < this->particles.size(); i++) {

pixel_color = pixels.getColor(this->particles[i]->get_location().x, this->particles[i]->get_location().y);

this->particles[i]->draw(this->particles, pixel_color);

}

this->fbo.end();

}

//--------------------------------------------------------------

void ofApp::draw() {

this->fbo.draw(0, 0);

}

//--------------------------------------------------------------

int main() {

ofSetupOpenGL(512, 512, OF_WINDOW);

ofRunApp(new ofApp());

}

#pragma once
#include "ofMain.h"

class Particle
{
public:
	Particle();
	~Particle() {};

	void apply_force(ofVec2f force);
	void update();
	void draw(vector<shared_ptr<Particle>> particles, ofColor body_color);

	ofVec2f get_location();
private:
	ofVec2f location;
	ofVec2f velocity;
	ofVec2f acceleration;
};

#pragma once

#include "ofMain.h"

class Particle

{

public:

Particle();

~Particle() {};

void apply_force(ofVec2f force);

void update();

void draw(vector<shared_ptr<Particle>> particles, ofColor body_color);

ofVec2f get_location();

private:

ofVec2f location;

ofVec2f velocity;

ofVec2f acceleration;

};

#include "Particle.h"

Particle::Particle() {
	this->location = ofVec2f(ofRandom(ofGetWidth()), ofRandom(ofGetHeight()));
	this->velocity = ofVec2f(ofRandom(-3, 3), ofRandom(-3, 3));
	this->acceleration = ofVec2f();
}

void Particle::apply_force(ofVec2f force) {
	this->acceleration += force;
}

void Particle::update() {
	this->acceleration += this->velocity;
	this->location += this->acceleration;
	this->acceleration *= 0;

	if (this->location.x < 0) {
		this->location.x = 0;
		this->velocity.x *= -1;
	}
	else if (this->location.x > ofGetWidth()) {
		this->location.x = ofGetWidth();
		this->velocity.x *= -1;
	}

	if (this->location.y < 0) {
		this->location.y = 0;
		this->velocity.y *= -1;
	}
	else if (this->location.y > ofGetHeight()) {
		this->location.y = ofGetHeight();
		this->velocity.y *= -1;
	}
}

void Particle::draw(vector<shared_ptr<Particle>> particles, ofColor body_color) {

	ofSetColor(body_color);
	ofDrawCircle(this->location, 3);

	float distance;
	for (int i = 0; i < particles.size(); i++) {
		distance = this->location.squareDistance(particles[i]->get_location());
		if (distance > 0 && distance < 300) {
			ofDrawLine(this->location, particles[i]->get_location());
		}
	}
}

ofVec2f Particle::get_location() {
	return this->location;
}

#include "Particle.h"

Particle::Particle() {

this->location = ofVec2f(ofRandom(ofGetWidth()), ofRandom(ofGetHeight()));

this->velocity = ofVec2f(ofRandom(-3, 3), ofRandom(-3, 3));

this->acceleration = ofVec2f();

}

void Particle::apply_force(ofVec2f force) {

this->acceleration += force;

}

void Particle::update() {

this->acceleration += this->velocity;

this->location += this->acceleration;

this->acceleration *= 0;

if (this->location.x < 0) {

this->location.x = 0;

this->velocity.x *= -1;

}

else if (this->location.x > ofGetWidth()) {

this->location.x = ofGetWidth();

this->velocity.x *= -1;

}

if (this->location.y < 0) {

this->location.y = 0;

this->velocity.y *= -1;

}

else if (this->location.y > ofGetHeight()) {

this->location.y = ofGetHeight();

this->velocity.y *= -1;

}

void Particle::draw(vector<shared_ptr<Particle>> particles, ofColor body_color) {

ofSetColor(body_color);

ofDrawCircle(this->location, 3);

float distance;

for (int i = 0; i < particles.size(); i++) {

distance = this->location.squareDistance(particles[i]->get_location());

if (distance > 0 && distance < 300) {

ofDrawLine(this->location, particles[i]->get_location());

}

ofVec2f Particle::get_location() {

return this->location;

}

[ Link ]
https://github.com/junkiyoshi/Insta20171206

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2017年11月20日2017年11月21日

Insta20171119

[ Video ]

[ About ]
カメラの画像をリアルタイムに識別しています。

Surface front camera images are classified in real time.

[ Source ]

#include <opencv2/dnn.hpp>
#include <opencv2/dnn/shape_utils.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
using namespace cv;
using namespace cv::dnn;

#include <fstream>
#include <iostream>
#include <algorithm>
#include <cstdlib>
using namespace std;

const size_t network_width = 416;
const size_t network_height = 416;

int main(int argc, char** argv)
{
	String modelConfiguration = "yolo.cfg";
	String modelBinary = "yolo.weights";
	dnn::Net net = readNetFromDarknet(modelConfiguration, modelBinary);
	if (net.empty()) {
		return -1;
	}

	cv::Mat frame, resized, inputBlob, detectionMat;
	cv::VideoCapture cap(0);
	if (!cap.isOpened()) {
		return -1;
	}

	vector<string> class_names = { "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train",
		"truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter",
		"bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear",
		"zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase",
		"frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
		"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle",
		"wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple",
		"sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut",
		"cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet",
		"tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave",
		"oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
		"teddy bear", "hair drier", "toothbrush" };

	while (true) {

		cap >> frame;
		cv::resize(frame, resized, cv::Size(network_width, network_height));
		inputBlob = blobFromImage(resized, 1 / 255.F);		//Convert Mat to batch of images
		net.setInput(inputBlob, "data");					//set the network input
		detectionMat = net.forward("detection_out");		//compute output

		float confidenceThreshold = 0.25;
		for (int i = 0; i < detectionMat.rows; i++)
		{
			const int probability_index = 5;
			const int probability_size = detectionMat.cols - probability_index;
			float *prob_array_ptr = &detectionMat.at<float>(i, probability_index);

			size_t objectClass = std::max_element(prob_array_ptr, prob_array_ptr + probability_size) - prob_array_ptr;
			float confidence = detectionMat.at<float>(i, (int)objectClass + probability_index);

			if (confidence > confidenceThreshold)
			{
				float x = detectionMat.at<float>(i, 0);
				float y = detectionMat.at<float>(i, 1);
				float width = detectionMat.at<float>(i, 2);
				float height = detectionMat.at<float>(i, 3);
				float xLeftBottom = (x - width / 2) * frame.cols;
				float yLeftBottom = (y - height / 2) * frame.rows;
				float xRightTop = (x + width / 2) * frame.cols;
				float yRightTop = (y + height / 2) * frame.rows;

				cv::Rect object(
					(int)xLeftBottom,
					(int)yLeftBottom,
					(int)(xRightTop - xLeftBottom),
					(int)(yRightTop - yLeftBottom));

				cv::Rect title(
					(int)xLeftBottom,
					(int)yLeftBottom - 15,
					(int)(xRightTop - xLeftBottom),
					15);

				std::string object_name = "";
				if (objectClass < class_names.size()) {
					object_name = class_names[objectClass];
				}
				cv::rectangle(frame, title, Scalar(0, 0, 255), -1);
				cv::putText(frame, object_name, cv::Point((int)xLeftBottom, (int)yLeftBottom - 2), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0), 2);
				cv::rectangle(frame, object, Scalar(0, 0, 255));
			}
		}

		imshow("detections", frame);
		waitKey(1);
	}

	return 0;
} // main

100

101

#include <opencv2/dnn.hpp>

#include <opencv2/dnn/shape_utils.hpp>

#include <opencv2/imgproc.hpp>

#include <opencv2/highgui.hpp>

using namespace cv;

using namespace cv::dnn;

#include <fstream>

#include <iostream>

#include <algorithm>

#include <cstdlib>

using namespace std;

const size_t network_width = 416;

const size_t network_height = 416;

int main(int argc, char** argv)

{

String modelConfiguration = "yolo.cfg";

String modelBinary = "yolo.weights";

dnn::Net net = readNetFromDarknet(modelConfiguration, modelBinary);

if (net.empty()) {

return -1;

}

cv::Mat frame, resized, inputBlob, detectionMat;

cv::VideoCapture cap(0);

if (!cap.isOpened()) {

return -1;

}

vector<string> class_names = { "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train",

"truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter",

"bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear",

"zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase",

"frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",

"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle",

"wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple",

"sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut",

"cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet",

"tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave",

"oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",

"teddy bear", "hair drier", "toothbrush" };

while (true) {

cap >> frame;

cv::resize(frame, resized, cv::Size(network_width, network_height));

inputBlob = blobFromImage(resized, 1 / 255.F); //Convert Mat to batch of images

net.setInput(inputBlob, "data"); //set the network input

detectionMat = net.forward("detection_out"); //compute output

float confidenceThreshold = 0.25;

for (int i = 0; i < detectionMat.rows; i++)

{

const int probability_index = 5;

const int probability_size = detectionMat.cols - probability_index;

float *prob_array_ptr = &detectionMat.at<float>(i, probability_index);

size_t objectClass = std::max_element(prob_array_ptr, prob_array_ptr + probability_size) - prob_array_ptr;

float confidence = detectionMat.at<float>(i, (int)objectClass + probability_index);

if (confidence > confidenceThreshold)

{

float x = detectionMat.at<float>(i, 0);

float y = detectionMat.at<float>(i, 1);

float width = detectionMat.at<float>(i, 2);

float height = detectionMat.at<float>(i, 3);

float xLeftBottom = (x - width / 2) * frame.cols;

float yLeftBottom = (y - height / 2) * frame.rows;

float xRightTop = (x + width / 2) * frame.cols;

float yRightTop = (y + height / 2) * frame.rows;

cv::Rect object(

(int)xLeftBottom,

(int)yLeftBottom,

(int)(xRightTop - xLeftBottom),

(int)(yRightTop - yLeftBottom));

cv::Rect title(

(int)xLeftBottom,

(int)yLeftBottom - 15,

(int)(xRightTop - xLeftBottom),

15);

std::string object_name = "";

if (objectClass < class_names.size()) {

object_name = class_names[objectClass];

}

cv::rectangle(frame, title, Scalar(0, 0, 255), -1);

cv::putText(frame, object_name, cv::Point((int)xLeftBottom, (int)yLeftBottom - 2), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0), 2);

cv::rectangle(frame, object, Scalar(0, 0, 255));

}

imshow("detections", frame);

waitKey(1);

}

return 0;

} // main

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Amazon

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2017年11月19日2017年12月5日

Insta20171118

[ Video ]

[ About ]
中心からの距離をNoise関数の引数にして、画素の高さを決めています。

The distance from the center is taken as an argument of the noise function, and the height of the pixel is determined.

[ Source ]

#include "ofMain.h"

class ofApp : public ofBaseApp {

public:
	void setup();
	void update();
	void draw();

	void keyPressed(int key) {};
	void keyReleased(int key) {};
	void mouseMoved(int x, int y) {};
	void mouseDragged(int x, int y, int button) {};
	void mousePressed(int x, int y, int button) {};
	void mouseReleased(int x, int y, int button) {};
	void mouseEntered(int x, int y) {};
	void mouseExited(int x, int y) {};
	void windowResized(int w, int h) {};
	void dragEvent(ofDragInfo dragInfo) {};
	void gotMessage(ofMessage msg) {};

	ofImage lenna;
	ofEasyCam cam;
};

#include "ofMain.h"

class ofApp : public ofBaseApp {

public:

void setup();

void update();

void draw();

void keyPressed(int key) {};

void keyReleased(int key) {};

void mouseMoved(int x, int y) {};

void mouseDragged(int x, int y, int button) {};

void mousePressed(int x, int y, int button) {};

void mouseReleased(int x, int y, int button) {};

void mouseEntered(int x, int y) {};

void mouseExited(int x, int y) {};

void windowResized(int w, int h) {};

void dragEvent(ofDragInfo dragInfo) {};

void gotMessage(ofMessage msg) {};

ofImage lenna;

ofEasyCam cam;

};

#include "ofApp.h"

//--------------------------------------------------------------
void ofApp::setup() {
	ofSetFrameRate(60);
	ofBackground(255);
	ofSetWindowTitle("Insta");

	ofSetDepthTest(true);

	this->lenna.loadImage("Lenna.png");
}

//--------------------------------------------------------------
void ofApp::update(){ }

//--------------------------------------------------------------
void ofApp::draw() {
	
	this->cam.begin();
	ofRotateZ(180);

	ofPixels pixels = this->lenna.getPixelsRef();
	ofColor pixel_color;
	float noise_value;
	float height;
	int size = 3;

	for (int x = 0; x < pixels.getWidth(); x += size) {
		for (int y = 0; y < pixels.getHeight(); y += size) {
			pixel_color = pixels.getColor(x, y);
			ofSetColor(pixel_color);

			float distance = ofVec2f(pixels.getWidth() / 2, pixels.getHeight() / 2).distance(ofVec2f(x, y));
			noise_value = ofNoise(distance * 0.008 + ofGetFrameNum() * 0.025);
			height = 300 * noise_value;

			ofDrawBox(ofVec3f(x - ofGetWidth() / 2, y - ofGetHeight() / 2, height / 2), size, size, height);
		}
	}

	this->cam.end();
}

//--------------------------------------------------------------
int main() {
	ofSetupOpenGL(512, 512, OF_WINDOW);
	ofRunApp(new ofApp());
}

#include "ofApp.h"

//--------------------------------------------------------------

void ofApp::setup() {

ofSetFrameRate(60);

ofBackground(255);

ofSetWindowTitle("Insta");

ofSetDepthTest(true);

this->lenna.loadImage("Lenna.png");

}

//--------------------------------------------------------------

void ofApp::update(){ }

//--------------------------------------------------------------

void ofApp::draw() {

this->cam.begin();

ofRotateZ(180);

ofPixels pixels = this->lenna.getPixelsRef();

ofColor pixel_color;

float noise_value;

float height;

int size = 3;

for (int x = 0; x < pixels.getWidth(); x += size) {

for (int y = 0; y < pixels.getHeight(); y += size) {

pixel_color = pixels.getColor(x, y);

ofSetColor(pixel_color);

float distance = ofVec2f(pixels.getWidth() / 2, pixels.getHeight() / 2).distance(ofVec2f(x, y));

noise_value = ofNoise(distance * 0.008 + ofGetFrameNum() * 0.025);

height = 300 * noise_value;

ofDrawBox(ofVec3f(x - ofGetWidth() / 2, y - ofGetHeight() / 2, height / 2), size, size, height);

}

this->cam.end();

}

//--------------------------------------------------------------

int main() {

ofSetupOpenGL(512, 512, OF_WINDOW);

ofRunApp(new ofApp());

}

[ Link ]
https://github.com/junkiyoshi/Insta20171118

[ほしいものリスト]
Amazon

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