Quasimondo

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

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

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

//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 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

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

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 torch
import torch.nn as nn
import torch.nn.functional as F

class LeakySine(nn.Module):
    def __init__(self, w0 =30.0, blend=0.75, slope = 0.2):
        super().__init__()
        self.blend = nn.Parameter(torch.ones(1, 1)*blend)
        self.slope = nn.Parameter(torch.zeros(1, 1)+slope)
        self.w0 = w0

Quasimondo

This is a dreaded error that seems pop up its ugly head again and again, in particular after upgrading CUDA or Tensorflow.
Typcially it looks like this:

2020-12-30 17:31:40.829615: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-12-30 17:31:42.149768: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 17:31:42.150368: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-12-30 17:31:42.176643: E tensorflow/stream_executor/cuda/cuda_driver.cc:328] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected

Here is a solution that currently seems to work on my system, 
with Cuda 11.0 and Tensorflow 2.4.0, you can try it if all the 

Quasimondo

'''
Usage:
python quickwatermark.py [path to folder that contains images to waternark]

This will go through all the files in that folder, try to open them and add 
the filename as text on top of the image. The watermarked images will be stored
in a subfolder of the chosen folder called "watermarked"

'''