작지만 성능 좋은 NAS를 만들자!
이런 목표를 가지고 아래의 기본 요구사항을 세웠다.
#include <iostream> | |
#include <vector> | |
#include <utility> | |
using namespace std; | |
// Reference | |
// https://learn.microsoft.com/ko-kr/cpp/cpp/move-constructors-and-move-assignment-operators-cpp?view=msvc-170 | |
class Block { | |
public: |
var cond_A = 1, cond_B = 2 | |
var ret_A = 10, ret_B = 20, ret_C = 30 | |
for (cond = 1; cond <= 3; cond ++) { | |
var ret = cond == cond_A ? ret_A : cond == cond_B ? ret_B : ret_C | |
print(cond, ret) | |
} | |
/* Return | |
1 10 |
function [Proj D radial tan r2] = ProjectPointRadial(P, R, T, f, c, k, p) | |
N = size(P,1); | |
X = R*(P'-T'*ones(1,N)); | |
XX = X(1:2,:)./([1; 1]*X(3,:)); | |
r2 = XX(1,:).^2 + XX(2,:).^2; | |
radial = 1 + dot(repmat(k',[1 N]), [r2; r2.^2; r2.^3], 1); | |
tan = p(1)*XX(2,:) + p(2)*XX(1,:); | |
XXX = XX.*repmat(radial+tan,[2 1]) + [p(2) p(1)]'*r2; | |
Proj = ones(N,1)*f .* XXX' + ones(N,1)*c; | |
D = X(3,:); |
import scipy.io | |
import numpy as np | |
FLIC = scipy.io.loadmat('FLIC/examples.mat') | |
filepath_idx = 1 | |
print(np.squeeze(np.squeeze(FLIC['examples']['filepath'])[filepath_idx])) | |
print(np.squeeze(np.squeeze(FLIC['examples']['imgdims'])[filepath_idx])) | |
print(np.squeeze(np.squeeze(FLIC['examples']['istrain'])[filepath_idx])) | |
coord = {'x': 0, 'y': 1} | |
print(np.squeeze(np.squeeze(np.squeeze(FLIC['examples'])[filepath_idx])['coords'])[coord['x']][7]) |
using System.Collections; | |
using System.Collections.Generic; | |
using UnityEngine; | |
public class ReadOnlyAttribute : PropertyAttribute | |
{ | |
} |