Quasimondo

40,5.770906432748538
78,5.923830409356725
83,7.939619883040936
87,5.833187134502924
118,5.39122807017544
125,5.565643274853802
196,7.127046783625732
200,5.97953216374269
250,5.631140350877193
254,7.2331871345029235

Quasimondo

import numpy as np
import cv2
import time
import torch
import torch.nn.functional as F

kernel = np.ones((41, 41) ).astype(np.float32)
cv_input = (np.random.random(size=(500,500))>0).astype(np.float32)

kernel_tensor = torch.Tensor(kernel).cuda().unsqueeze(0).unsqueeze(0)  

Quasimondo

import os
import numpy as np
import threading
from imageio import imwrite,imread
from scipy.ndimage import zoom

class Corona():
    def __init__(self):
        self.infectionProbability = 0.02
        self.lethalProbability = 0.02

Quasimondo

//g++ sdl_opengl_player.cpp $(pkg-config --cflags --libs libvlc sdl2 gl)

/* Licence WTFPL  */
/* Written by Pierre Lamot */

#include <stdio.h>
#include <stdlib.h>

#include <exception>
#include <mutex>

Quasimondo

import struct
import numpy as np

def afpk2peaks(peakfilename):
    PEAK_FMT = '<2i'
    PEAK_MAGIC = 'audfprintpeakV00'  # 16 chars, FWIW

    """ Read back a set of (time, bin) pairs written by peaks_save """
    peaks = []
    fmtsize = struct.calcsize(PEAK_FMT)

Quasimondo

import numpy as np


#input is a RGB numpy array with shape (height,width,3), can be uint,int, float or double, values expected in the range 0..255
#output is a double YUV numpy array with shape (height,width,3), values in the range 0..255
def RGB2YUV( rgb ):
     
    m = np.array([[ 0.29900, -0.16874,  0.50000],
                 [0.58700, -0.33126, -0.41869],
                 [ 0.11400, 0.50000, -0.08131]])

Quasimondo

Verifying that +quasimondo is my openname (Bitcoin username). https://onename.io/quasimondo