This is converted for for US measurements. I will also have my develop times on here.
Page 7 of the manual converted. This assumes you have the following US-based measurement devices:
| #include <iostream> | |
| #include <SDL/SDL.h> | |
| int main(int argc, char * argv[]) | |
| { | |
| // Initialize SDL with video | |
| SDL_Init(SDL_INIT_VIDEO); | |
| // Create a window with SDL |
| struct ogl_backend | |
| { | |
| typedef unsigned texture_handle_type; | |
| void load(texture_handle_type& texture, const Image& image) | |
| { | |
| std::cout << "loading, " << image.id << '\n'; | |
| } | |
| void destroy(texture_handle_type& texture) |
| import random | |
| HEADS = 0 | |
| TAILS = 1 | |
| n = input("How many samples do you wish to compute?: ") | |
| p = random.random() | |
| print "probability of getting heads is:", p |
| #include <iostream> | |
| #include <vector> | |
| #include <list> | |
| #include <cstdlib> | |
| #include <algorithm> | |
| #include <functional> | |
| #include <chrono> | |
| int entries = 10000; |
| #include <chrono> | |
| #include <cstdint> | |
| #include <iostream> | |
| #include <random> | |
| #include <sstream> | |
| using namespace std; | |
| typedef std::chrono::microseconds time_unit; | |
| static const std::string time_unit_suffix{"us"}; |
| #include <iostream> | |
| #include <algorithm> | |
| #include <vector> | |
| #include <array> | |
| template <typename RandomIt> | |
| void insertion_sort(RandomIt begin, RandomIt end) | |
| { | |
| // loop through all the elements, from | |
| // the the second element to the last. |
| #include <iostream> | |
| #include <tuple> | |
| template<template <typename T> class X> | |
| struct Wrap | |
| { | |
| template <typename T, typename... Args> | |
| struct Deducer | |
| { | |
| typedef decltype(std::tuple_cat(std::tuple<X<T>>(), typename Deducer<Args...>::tuple())) tuple; |
| from keras.utils import plot_model | |
| from keras.models import Model | |
| from keras.layers import Input, Dense, concatenate | |
| def create_inner_model(): | |
| input=Input((10,)) | |
| d1 = Dense(128)(input) | |
| d2 = Dense(64)(d1) |
| gradio | |
| torch | |
| git+https://github.com/facebookresearch/segment-anything.git | |
| git+https://github.com/openai/CLIP.git | |
| opencv-python |