hirocarma

import os
import sys
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
import cv2


def wav_to_image_with_rgb(wav_file, image_file):
    sample_rate, data = wavfile.read(wav_file)

hirocarma

import os
import sys
import cv2
import numpy as np
from scipy.io import wavfile
from scipy.signal import firwin, lfilter
from scipy.signal.windows import hamming
import matplotlib.pyplot as plt

hirocarma

#!/usr/bin/env python
from PIL import Image, ImageDraw, ImageFont
import matplotlib.colors as mcolors
import colorsys
import cv2
import numpy as np
from scipy.spatial import KDTree

height = 100
width = 600

hirocarma

#!/usr/bin/env python
import numpy as np
from scipy.io.wavfile import write
import matplotlib.pyplot as plt

sample_rate = 44100
duration = 10


def generate_blue_noise(duration, sample_rate):

hirocarma

#!/usr/bin/env python
import sys
import numpy as np
import matplotlib.pyplot as plt
import wave
import scipy.signal as signal
import math

LIMIT_DB = 20
MAX_DB = 85

hirocarma

#!/usr/bin/env python
import cv2
import numpy as np
import sys
import os
import math

CANVAS_WIDTH, CANVAS_HEIGHT = 1920, 1080
BASE_SIZE = (640, 360)
TARGET_SIZE = (160, 90)

hirocarma

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import cv2
import sys
import numpy as np
import math
import shutil
import json
from sklearn.cluster import DBSCAN

hirocarma

#!/usr/bin/env python
import os
import sys
import cv2
import numpy as np
import colorsys
import matplotlib.pyplot as plt
import math
from scipy import stats
import matplotlib.patches as patches