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 = 400

hirocarma

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

height = 200
width = 400
txt_x = 2

hirocarma

from PIL import Image, ImageDraw

height = 300
width = 600
txt_x = 2
txt_y = 2
txt_color = "red"


def color_save(text, color_rgb):

hirocarma

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#--- description
# Using  WebRTC Voice Activity Detector (VAD)  model,
# extract the periods of time a person is speaking
# from the audio file and calculate the percentage.
#--- reference
# https://webrtc.org/
# https://github.com/wiseman/py-webrtcvad/tree/master

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 = 70

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
from scipy.interpolate import interp1d
LIMIT_dB = 20

hirocarma

import os
import sys
import shutil
import cv2
import numpy as np

def main():
    IMG_DIR = sys.argv[1]
    OUT_DIR = sys.argv[2]
    height = 1080

hirocarma

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

def main():
    img_file1 = sys.argv[1]

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
from scipy.interpolate import interp1d
LIMIT_dB = 20

hirocarma

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

def main():
    IMG1_DIR = sys.argv[1]
    IMG2_DIR = sys.argv[2]