keizerzilla

#include <stdio.h>

#define KNRM  "\x1B[0m"
#define KRED  "\x1B[31m"
#define KGRN  "\x1B[32m"
#define KYEL  "\x1B[33m"
#define KBLU  "\x1B[34m"
#define KMAG  "\x1B[35m"
#define KCYN  "\x1B[36m"
#define KWHT  "\x1B[37m"

keizerzilla

import numpy as np


def normalize_to_smallest_integers(labels):
    """Normalizes a list of integers so that each number is reduced to the minimum possible integer, maintaining the order of elements.

    :param labels: the list to be normalized
    :returns: a numpy.array with the values normalized as the minimum integers between 0 and the maximum possible value.
    """

keizerzilla

def gera_amostras(dados, k_vizinhos=5, k_amostras=5):
    """
    
    Simples gerador de amostras sintéticas a partir de distâncias. A partir de duas
    amostras P e Q do conjunto de k_amostras, gera uma terceira R igual ao ponto médido
    de P e Q.
    Requisitos: numpy scikit-learn.
    
    Parâmetros
    ----------

keizerzilla

# camlist.py
# Lists all avaiable cameras attached to the computer
# Dependencies: pip install opencv-python
# Usage: python camlist.py

import cv2

print(f"OpenCV version: {cv2.__version__}")

max_cameras = 10