naoya-chiba

#define _CRT_SECURE_NO_WARNINGS

#include <string>
#include <tuple>
#include <Eigen/Core>
#include <pcl/io/ply_io.h>
#include <pcl/point_cloud.h>
#include <pcl/common/transforms.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/features/normal_3d.h>

paniq

# forays into
    Perfect Spatial Hashing (Lefebvre & Hoppe)
    http://hhoppe.com/perfecthash.pdf

    how it works:

    There are two parts: a slow encoding step, and a fast decoding step.

    Encoding

gocarlos

// A simple quickref for Eigen. Add anything that's missing.
// Main author: Keir Mierle

#include <Eigen/Dense>

Matrix<double, 3, 3> A;               // Fixed rows and cols. Same as Matrix3d.
Matrix<double, 3, Dynamic> B;         // Fixed rows, dynamic cols.
Matrix<double, Dynamic, Dynamic> C;   // Full dynamic. Same as MatrixXd.
Matrix<double, 3, 3, RowMajor> E;     // Row major; default is column-major.
Matrix3f P, Q, R;                     // 3x3 float matrix.

devteampentagon

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.List;

/**
 * http://www.geeksforgeeks.org/closest-pair-of-points-onlogn-implementation/
 * https://www.youtube.com/watch?v=_pSl90jq-m0 another good explanation
 * Given coordinates of points find closest pair points distance.
 * 

pixelmager

Use cases

• Bluenoise in the game INSIDE (dithering, raymarching, reflections)
• Dithering, Ray marching, shadows etc
• A Survery of Blue Noise and Its Applications

Textures/Matrices for direct use (data!)

• Moments In Graphics (void-and-cluster)
  • 2D
  • 3D and 4D
• Bart Wronski Implementation of Solid Angle algorithm

kyrs

/*
  Following file take opencv mat file as an input and convert it to proper tensor object 
  Created by : Kumar Shubham
  Date : 27-03-2016
*/

//Loading Opencv fIles for processing

//#include <opencv2/opencv.hpp>

kyrs

/*
  Following file take opencv mat file as an input and run inception model on it
  Created by : Kumar Shubham
  Date : 27-03-2016
*/

//Loading Opencv fIles for processing

#include <opencv2/opencv.hpp>

royshil

/// perform the Simplest Color Balancing algorithm
void SimplestCB(Mat& in, Mat& out, float percent) {
    assert(in.channels() == 3);
    assert(percent > 0 && percent < 100);

    float half_percent = percent / 200.0f;

    vector<Mat> tmpsplit; split(in,tmpsplit);
    for(int i=0;i<3;i++) {
        //find the low and high precentile values (based on the input percentile)

ialhashim

#pragma once

// Code adapted from https://github.com/propanoid/DBSCAN

#include <vector>
#include <algorithm>
#include <omp.h>

// Any basic vector/matrix library should also work
#include <Eigen/Core>

paultsw

boundingSphere :: [(Float,Float,Float)] -> ((Float,Float,Float),Float)      --takes a list of points in 3D to a pair (center,radius)
boundingSphere points =
	case points of 					--induction on number of points: 0,1,2, or 3+
		[] 				->	((0,0,0),0)
		p:[] 				->	(p,0)
		(p1,p2,p3):(q1,q2,q3):[] 	->	(((p1+q1)/2,(p2+q2)/2,(p3+q3)/2),dist (p1,p2,p3) (q1,q2,q3))
		p:pts				->	let
								y@(y1,y2,y3) = head $ filter (\pt -> (dist pt p) - 0.1 < (maximum $ map (dist p) pts)) pts
								z@(z1,z2,z3) = head $ filter (\pt -> (dist pt y) - 0.1 < (maximum $ map (dist y) pts)) pts
								initSphere@(ctr,rad) = (((y1+z1)/2, (y2+z2)/2, (y3+z3)/2), dist y z / 2)