dmateos

#include <stdbool.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>

#define PROGRAM_SIZE 1024
#define STACK_SIZE 1024

dmateos

#include <stdbool.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>

#define PROGRAM_SIZE 1024

enum INSTRUCTIONS {

dmateos

package main

import (
	"bufio"
	"fmt"
	"os"
	"strconv"
	"strings"
)

dmateos

import React from 'react';
import logo from './logo.svg';
import './App.css';

import { useState, useEffect } from 'react';
import { Amplify } from 'aws-amplify';
import { generateClient } from 'aws-amplify/api';
import { listPersons } from './graphql/queries';
import { Person } from "./API";

dmateos

import cv2
import os
from PIL import Image
from torchvision.models.detection import fasterrcnn_resnet50_fpn_v2, FasterRCNN_ResNet50_FPN_V2_Weights
from torchvision.transforms.functional import pil_to_tensor

cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)  # width
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)  # height
cap.set(cv2.CAP_PROP_FPS, 30)  # frame rate

dmateos

import cv2
import numpy as np
from matplotlib import pyplot as plt

#IMAGE = "circle.jpg"
IMAGE = "lisa.png"
#IMAGE = "melita.png"
INITIAL_POPULATION = 500
EPOCHS = 128
DNA_LENGTH = 1024

dmateos

import cv2
import numpy as np
from matplotlib import pyplot as plt

IMAGE = "circle.jpg"
#IMAGE = "lisa.png"
#IMAGE = "melita.png"
INITIAL_POPULATION = 500
EPOCHS = 128
DNA_LENGTH = 64

dmateos

#include "main.h"

#include <SDL2/SDL.h>
#include <cglm/cglm.h>
#include <png.h>
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>

typedef struct {

dmateos

#include "main.h"

#include <SDL2/SDL.h>
#include <cglm/cglm.h>
#include <math.h>
#include <stdio.h>  
#include <stdlib.h>
#include <unistd.h>

#include "utils.h"

dmateos

#include "main.h"

#include <SDL2/SDL.h>
#include <cglm/cglm.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>

#include "utils.h"